2d:Tb97,# A loop that cannot stop is an invoice You're in the agent studio. **What you're doing this lesson:** give the AI helper a stop rule — a maximum number of steps and a maximum spend — so a stuck retry cannot become an invoice. You do not need to have shipped loops at work to start. A **loop** here means: look at the failing job, try one action, look again, repeat. Without a stop rule, "again" never ends. That's the triage helper from the last lesson, stripped of mystique: look at the state, pick one allowed action, check it, run it, write down the result, go again. A person deciding "try once more" is cheap. A model deciding the same thing, on a real API bill plus real CI compute (the automated tests that run when someone pushes code), with an exit condition of "the model feels done," is not. The model does not reliably feel done. Here's the failure you'll actually see: job `j-118` is red because a dependency registry is having a bad day. The agent reads the log, decides flake (a test that fails randomly), reruns. Still red — the registry is still down. Reads the log again. Same log. Reruns again. Every iteration looks *locally reasonable*; the run as a whole is a money fire. No single step is a bug you could point to in review. The bug is that nothing above the steps is counting. ## The two caps, and why they're both mandatory - **Step cap.** A hard ceiling on iterations. Triage should finish in six steps; a run at step seven isn't being thorough, it's stuck. The cap converts "stuck" from a silent state into a named outcome you can alert on. - **Cost cap.** Steps aren't priced equally — reading a log tail is pennies, rerunning a job is compute. A run can be four steps long and still be too expensive if three of them are reruns. The cost cap meters dollars, not iterations, and fires *before* the overspending call runs, not after. You need both. A step cap alone lets six expensive steps through. A cost cap alone lets forty cheap steps loop forever below the price ceiling. They fail differently, so they gate differently. ## Stop reasons are part of the return value The lazy loop returns its answer or nothing. Yours returns *why it stopped*, every time, as a short label from a closed set: `plan-complete`, `step-cap`, `cost-cap`. This is the same idea as an exit code on a program — "done" versus "killed" — and you'd never ship a service that couldn't tell you which. The distinction earns its keep in the metrics, a week after launch. `plan-complete` trending down while `step-cap` trends up means your agent is getting lost more — maybe a prompt regression, maybe a new failure mode in the queue. `cost-cap` firing at all means some job class is eating reruns. You can only see the trend if the loop names the reason, and the loop can only name the reason if the caps are inside the loop definition — not a wrapper someone adds after the first incident, because by then the first incident has happened.2e:T876,# Caps are two lines at the top of the loop body Run the code. That's the whole pattern — a metered loop in under twenty lines, and the two lines that matter are the first two inside the `for`. Three details are load-bearing, and all three are the kind of thing that looks pedantic until it pages you: **The cost check runs *before* the spend.** `spent + COST[tool] > cap` asks "would this call bust the budget?" — not "did the last one?" Check after the spend and your cap is a tripwire you discover you crossed one `rerun_job` too late. With real money, "detected the overage" and "prevented the overage" are different features. Build the second one. **The checks precede the work in every iteration.** Not once before the loop, not in a wrapper around it — at the top of every pass. The plan here is fixed, but in the real loop the model picks the next tool *each* iteration based on the last result, so cost accrues one decision at a time. The gate has to sit where the decisions happen. **`for/else` gives plan-complete for free.** The `else` arm runs only when the loop exhausts the plan without a `break` — which is precisely the definition of "finished on its own." The three exits produce three distinct stop reasons, each printed from exactly one place. When a run ends, there is no ambiguity about which door it left through. ## Scripted plans, real logic One honest note on the drills in this lesson: the `plan` list stands in for the model. In production, each iteration calls `messages.create`, the model looks at the tool results so far and proposes the next call, and *that* proposal is what streams through your validator and your caps. Scripting the plan removes the nondeterminism so the thing under test is your metering logic — the part that doesn't change when you swap models. That's not a toy simplification; it's the actual boundary. The caps don't care whether the next tool call came from Opus, from a cheaper model, or from a list. Neither does the validator from lesson 1. Everything you're building in this studio lives on your side of the API call, which is why all of it survives your next model migration untouched.2f:Ta35,# The trace is the receipt Bug report, day two of the feature: "the agent filed a p1 for an npm 503 instead of just rerunning — and why did nobody get paged?" Your move is not to reread the prompt, and it is definitely not to rerun the agent and hope it misbehaves again. Nondeterministic systems don't grant you a repro. Your move is to open the trace. Run the code. Four dicts, one per step: tool, validator verdict, result, running spend. Reading it top to bottom answers the bug report in about fifteen seconds: the agent *did* read the log, *did* see the 503, then proposed `escalate` — arguably right for a registry outage blocking all of CI — got rejected for missing confirmation, and fell back to `open_issue` at p1. Nobody got paged because the confirm gate held (working as designed) and the p1 happened because the fallback path doesn't downgrade severity (the actual bug, and it's in your routing logic, not the model). Without the trace, that same investigation is an afternoon of rereading a chat transcript and speculating about model intent. The transcript can't tell you whether the agent retrieved the wrong data, called the wrong tool, or reasoned badly over good inputs. The trace can — it's the recorded story of one run: what came in, what was decided, what was called, what it cost. ## Trace-first is a discipline, not a log level Three rules, all cheap now and expensive to retrofit: - **The loop writes the trace; humans don't.** Every iteration appends its record as a side effect of running — tool, verdict, result, spend. If tracing is a thing someone remembers to add, the run you need traced is the run that didn't have it. In production this is a JSONL file or an OTel span per step; the schema is exactly the dict you just read. - **Record verdicts, not just actions.** Step 3 is the most informative line in this trace and *nothing executed* — a rejected call that never ran. Log only what succeeded and the story reads "read log, opened issue," which hides the entire plot: the agent wanted to page a human and your gate said no. Rejections are evidence of the model's intent colliding with your contract. That collision is usually where the bug lives. - **No secrets in the trace.** The trace outlives the run — it lands in log aggregators, bug reports, that Slack thread with a screenshot. Tool results carry log tails; log tails love to carry tokens. Redact at write time, because you don't control who reads it later. Debug from the trace first, the code second, the prompt third. The order matters: the trace tells you *which* of the other two to open.30:T4b0,Checkpoint: bolt lesson 1 onto lesson 2. Write `triage_run(plan, caps)` where each plan entry is a *call dict* (`{"tool": ..., "confirmed": ...}`), and every iteration goes: step cap → validate → cost gate → spend and run. Rules, in order per iteration: 1. Step number over `caps["max_steps"]` → print `stop: step-cap ($X.XX spent)` and return. 2. Look up the tool's spec in `TOOLS`. If it needs confirm and the call lacks a truthy `confirmed` → print `step N: reject: needs confirm` — the same verdict string your validator returns — and continue to the next call. A rejected call burns a step but spends nothing; the validator said no before anything ran. 3. If `spent + cost` exceeds `caps["max_cost_usd"]` → print `stop: cost-cap ($X.XX spent)` and return. 4. Otherwise spend and print `step N: ok $X.XX`. Plan exhausted → `stop: plan-complete ($X.XX spent)`. Expected output (two runs): ``` step 1: read_log_tail ok $0.03 step 2: rerun_job reject: needs confirm step 3: rerun_job ok $0.14 step 4: open_issue ok $0.18 stop: plan-complete ($0.18 spent) step 1: rerun_job ok $0.11 step 2: rerun_job ok $0.22 stop: cost-cap ($0.22 spent) ``` 31:T4f9,TOOLS = { "read_log_tail": {"confirm": False, "cost": 0.03}, "rerun_job": {"confirm": True, "cost": 0.11}, "open_issue": {"confirm": False, "cost": 0.04}, } def triage_run(plan, caps): spent = 0.0 for i, call in enumerate(plan, 1): if i > caps["max_steps"]: print(f"stop: step-cap (${spent:.2f} spent)") return spec = TOOLS[call["tool"]] if spec["confirm"] and not call.get("confirmed"): print(f"step {i}: {call['tool']} reject: needs confirm") continue if spent + spec["cost"] > caps["max_cost_usd"]: print(f"stop: cost-cap (${spent:.2f} spent)") return spent += spec["cost"] print(f"step {i}: {call['tool']} ok ${spent:.2f}") print(f"stop: plan-complete (${spent:.2f} spent)") triage_run( [ {"tool": "read_log_tail"}, {"tool": "rerun_job"}, {"tool": "rerun_job", "confirmed": True}, {"tool": "open_issue"}, ], {"max_steps": 6, "max_cost_usd": 0.50}, ) triage_run( [ {"tool": "rerun_job", "confirmed": True}, {"tool": "rerun_job", "confirmed": True}, {"tool": "rerun_job", "confirmed": True}, ], {"max_steps": 6, "max_cost_usd": 0.25}, ) 32:Tc06,# Wire the evals before the feature "works" You're in the agent studio. **What you're doing this lesson:** write a few real past incidents as test cases *before* you trust the helper to route new ones. Green on those cases is what "works" means. You do not need a test-driven-development habit to start. An **eval** here is a scored test of the helper's behavior: given this past incident, did it pick the route a human already paid to learn? A **golden case** is one of those past incidents plus the routing decision that was right for it, verified by whoever handled it. ``` ("G2", "prod deploy failed healthcheck", "escalate") ``` That case is not hypothetical. That's the Tuesday production (the live system customers use) went down and the on-call (the person whose phone rings) found out from a customer because some earlier automation filed a low-priority issue instead of paging. The case encodes the lesson so the eval runner re-teaches it to every future version of the router, forever, for free. ## Why "before it works" is the load-bearing part The order of operations is the whole discipline: 1. Collect four or five real incidents from CI history (the automated test runs). Write each as `(id, job_text, correct_route)`. 2. Write the eval runner — a loop that routes each case and prints pass/FAIL with a summary. 3. *Now* write the routing logic, and keep going until the runner says `4/4 — ship`. Do it in this order and "done" has a definition a script can check. Do it in the other order — feature first, evals someday — and "done" means "the three cases I tried by hand looked right," which is how the npm-503 case (the JavaScript package registry was temporarily down) ends up opening a noisy issue on launch day instead of a quiet rerun. There's a second-order effect too: writing the cases first *changes the routing logic you write*. Stare at "npm registry 503 during install → rerun" before coding and you'll never write a router that only checks for the word "timeout." The eval set is a spec you can execute, and specs you write after shipping are just documentation of the bugs. ## What golden cases are not - **Not a benchmark.** You're not measuring the model against the field; you're checking *your feature* still makes the calls your team already paid to learn. - **Not proof of future behavior.** Four green cases mean the router handles four known situations. The queue will invent a fifth — that's what the ratchet at the end of this lesson is for. - **Not big.** Four to a dozen cases per feature, each one earned by an incident. A thousand synthetic cases nobody can vouch for is worse than five real ones someone can, because when a synthetic case fails you argue about the case instead of fixing the router. The eval run becomes your ship gate: green means deploy, red means the feature — not the test — needs work. Same idea as any test suite you already trust, aimed at the helper's behavior instead of your own code. The rest of this lesson builds the runner, turns it red, and makes it green the honest way.33:T973,# A golden case is a past incident with a verdict Run the code. Twelve lines of data, and every line has a story. G2 is the outage where a p3 issue quietly absorbed a prod incident. G4 is the 2 a.m. page for a registry blip that fixed itself before the on-call's laptop finished waking up. The golden set is your team's incident history, compiled to something executable. Each case is three fields — id, input, expected route. The `FORBIDDEN` table adds the sharper edge: the route that must *never* fire, with the incident that taught you. Expected-route checks catch wrong answers; forbidden-route checks catch *expensive* wrong answers. "G4 should rerun" failing to `open_issue` is noise in the tracker. Failing to `escalate` is a human awake at 2 a.m. — same wrong answer count, very different postmortem, and your eval output should distinguish them. ## Where cases come from, in practice - **Grep CI history for the incidents that had consequences.** The failure that ate an afternoon, the page that shouldn't have fired, the flake that got a real bug ignored. Consequences are what make a case worth its slot. - **One case per failure *mode*, not per failure.** You don't need forty timeout cases; you need one timeout, one registry 503, one prod healthcheck, one honest assertion failure. Coverage of modes beats volume of examples. - **The expected answer comes from the human who handled it.** Not from running the router and freezing whatever it said — that's how you enshrine today's bugs as tomorrow's spec. If nobody can say what the right call was, it isn't a golden case yet; it's a discussion for standup. ## The set only grows One rule turns this from a test file into an asset: **cases are never deleted to make the run green.** A case that fails after a change is the eval doing its job; the router changes, not the history. Deleting G4 because it's inconvenient is deleting the memory of the 2 a.m. page — and booking a repeat. Cases get *added* on a trigger you'll drill at the end of this lesson: every new incident becomes a new case the day it happens. Ship week one with four cases; a quarter of real traffic later you have fifteen, each one a mistake the feature can no longer repeat without a red run telling on it. That accumulation is the ratchet — and it's the difference between a feature that ages into reliability and one that stays exactly as trustworthy as its demo.34:Tc46,# Every rule traces back to a failure The fix you just shipped — the 503 clause — will be a mystery in six months. Someone will read `or "503" in text`, wonder if it's dead code, and delete it in a refactor. The eval case G4 will catch the regression, but now you're relitigating a solved incident. The ratchet log exists so solved stays solved. Osmani's rule, lightly paraphrased — his exact wording in *Agent Harness Engineering* is "every line in a good AGENTS.md should be traceable back to a specific thing that went wrong" — and the discipline worth pinning above your desk: **every line in a good system prompt traces back to a specific, historical failure.** Same standard for your harness config, your tool contract, your routing rules. Run the code — each entry pairs a rule with the failure that earned it. Not "be robust to registry errors." A dated incident: forty issues, zero reruns, here's what changed. ## Five fields, none optional - **`date`** — anchors the entry to the session where it happened, so you can find the trace (lesson 2 just made sure there is one) and replay the run. - **`failure`** — the specific narrated event, one sentence. If you can't write the sentence, you're about to add a cargo-cult rule. Go reproduce the failure first, or don't add the rule. - **`rule`** — phrased as an action with concrete strings, commands, values. "Be careful with reruns" is a vibe. "`rerun_job` max once per job per run" is enforceable, and you can tell at review time whether a change violates it. - **`artifact`** — *where the rule lives*: an AGENTS.md line, a hook, a validator branch, a golden case. The best entries land in two places — the text is the explanation for the model, the code is the enforcement. Note both entries above name a golden case or a cap as their enforcement half. - **`remove_when`** — the exit condition, and the most-skipped field in the industry. A rule with no exit condition is permanent, and permanent rules are debt: eighteen months from now half your config will be workarounds for model behaviors that no longer exist, each one taxing attention on every run. Write the exit the day you write the rule, even if it feels speculative. ## The incident routine, end to end New failure in production. The routine is four moves, maybe twenty minutes: 1. **Pull the trace.** Find the step where it went wrong — verdict, result, spend. 2. **Add the golden case.** The incident becomes `("G5", ..., correct_route)`. The eval run goes red. Good — red is the incident, preserved. 3. **Fix until green.** Router, contract, caps — whichever artifact the trace implicates. 4. **Append the ratchet entry.** Five fields, linking the failure to the rule to the artifact to the exit condition. Append-only, audited quarterly, entries retired only when their `remove_when` comes true — and the retirement itself gets logged. Run this routine for a quarter and your harness is measurably better than at launch, no model upgrade required. Skip it and you have the same agent in month six that you had in week one, plus a pile of hotfixes nobody can explain in review.35:T482,ENTRIES = [ ("R1", {"date": "2026-07-14", "failure": "agent reran j-118 four times on one red build, $0.44 burned", "rule": "rerun_job max once per job per run; second red goes to open_issue", "artifact": "AGENTS.md line 31 + cost cap in loop", "remove_when": "provider ships native per-tool rate limits"}), ("R2", {"date": "2026-07-18", "failure": "agent opened p3 issue for a prod healthcheck failure", "rule": "any job text containing 'prod' routes to escalate, never open_issue", "artifact": "route() prod branch + golden case G2", "remove_when": ""}), ("R3", {"date": "2026-07-21", "failure": "agent reran a deploy job mid-incident", "rule": "Be careful with reruns during incidents", "artifact": "AGENTS.md line 40", "remove_when": "incident-mode flag lands in the harness"}), ] # define lint_entry(entry) below ok = 0 for rid, entry in ENTRIES: verdict = lint_entry(entry) ok += verdict == "ok" print(f"{rid} {verdict}") print(f"{ok}/{len(ENTRIES)} entries earned their line") 36:T572,ENTRIES = [ ("R1", {"date": "2026-07-14", "failure": "agent reran j-118 four times on one red build, $0.44 burned", "rule": "rerun_job max once per job per run; second red goes to open_issue", "artifact": "AGENTS.md line 31 + cost cap in loop", "remove_when": "provider ships native per-tool rate limits"}), ("R2", {"date": "2026-07-18", "failure": "agent opened p3 issue for a prod healthcheck failure", "rule": "any job text containing 'prod' routes to escalate, never open_issue", "artifact": "route() prod branch + golden case G2", "remove_when": ""}), ("R3", {"date": "2026-07-21", "failure": "agent reran a deploy job mid-incident", "rule": "Be careful with reruns during incidents", "artifact": "AGENTS.md line 40", "remove_when": "incident-mode flag lands in the harness"}), ] def lint_entry(entry): for field in ("date", "failure", "rule", "artifact", "remove_when"): if not entry.get(field): return f"reject: missing {field}" if "be careful" in entry["rule"].lower(): return "reject: vibes rule" return "ok" ok = 0 for rid, entry in ENTRIES: verdict = lint_entry(entry) ok += verdict == "ok" print(f"{rid} {verdict}") print(f"{ok}/{len(ENTRIES)} entries earned their line") 37:T4e1,Final checkpoint — the ship gate, run twice in one sitting, exactly the way it runs in real life. Write `ship_gate(golden)`: - For each case, route the job text and compare to the expected route. Match → print ` pass`. - Miss → check `FORBIDDEN`: if the route it *did* pick is that case's must-never route, print ` FAIL (forbidden: )`. Any other miss is plain ` FAIL`. Wrong is wrong, but the expensive kind of wrong gets named. - All green → final line `N/N SHIP`. - Any red → `P/N HOLD (K failing)` where K is the number failing. Then the plot: run the gate on the four-case set (it's green — the 503 fix from earlier is in). A new incident lands: runner 7's disk has been full for three days, and each day the agent filed another issue instead of paging infra. Append `("G5", "runner disk full for the third day", "escalate")`, record the route that caused the incident — `FORBIDDEN["G5"] = "open_issue"` — and run the gate again. The set only grows, and today's SHIP becomes HOLD with a FAIL line naming the exact mistake the router keeps making. Expected output: ``` G1 pass G2 pass G3 pass G4 pass 4/4 SHIP G1 pass G2 pass G3 pass G4 pass G5 FAIL (forbidden: open_issue) 4/5 HOLD (1 failing) ``` 38:T4ea,def route(job): text = job.lower() if "prod" in text or "security" in text: return "escalate" if "timeout" in text or "connection reset" in text or "503" in text: return "rerun" return "open_issue" GOLDEN = [ ("G1", "unit test timeout on runner 3", "rerun"), ("G2", "prod deploy failed healthcheck", "escalate"), ("G3", "assertion error in cart total", "open_issue"), ("G4", "npm registry 503 during install", "rerun"), ] FORBIDDEN = { # route that must NEVER fire for this case — each line earned by an incident "G2": "open_issue", "G4": "escalate", } def ship_gate(golden): passed = 0 for cid, job, want in golden: got = route(job) ok = got == want passed += ok if ok: print(f"{cid} pass") elif got == FORBIDDEN.get(cid): print(f"{cid} FAIL (forbidden: {got})") else: print(f"{cid} FAIL") if passed == len(golden): print(f"{passed}/{len(golden)} SHIP") else: print(f"{passed}/{len(golden)} HOLD ({len(golden) - passed} failing)") ship_gate(GOLDEN) GOLDEN.append(("G5", "runner disk full for the third day", "escalate")) FORBIDDEN["G5"] = "open_issue" ship_gate(GOLDEN) 1c:[["$","$L24",null,{"payload":{"catalog":"The loop with a meter — budget caps, stop reasons, and the trace (step 3/8) · agent studio · promptdojo","byPath":{"developer":"The loop with a meter — budget caps, stop reasons, and the trace (step 3/8) · agent studio · promptdojo"}}}],["$","script",null,{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"$25"}}],["$","$L26",null,{"tree":{"toc":{"version":"0.1.0","generatedAt":"1970-01-01T00:00:00.000Z","chapters":[{"number":0,"slug":"before-you-build","title":"from worker to builder","blurb":"stop doing repeated work by hand. this chapter is the map: the builder loop, old workplace deliverables turned into site artifacts, and the reusable tool card. if you are starting here, 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,"lessons":[{"slug":"the-tool-contract","steps":[{"id":"agent-studio/the-tool-contract/s01-01-the-feature-you-ship-today"},{"id":"agent-studio/the-tool-contract/s02-02-the-schema-is-the-blast-radius"},{"id":"agent-studio/the-tool-contract/s03-03-spot-the-loose-tool"},{"id":"agent-studio/the-tool-contract/s04-04-predict-the-validation"},{"id":"agent-studio/the-tool-contract/s05-05-fix-the-yolo-rerun"},{"id":"agent-studio/the-tool-contract/s06-06-write-validate-call"},{"id":"agent-studio/the-tool-contract/s07-07-checkpoint"}]},{"slug":"the-loop-with-a-meter","steps":[{"id":"agent-studio/the-loop-with-a-meter/s01-01-a-loop-that-cannot-stop-is-an-invoice"},{"id":"agent-studio/the-loop-with-a-meter/s02-02-caps-are-part-of-the-loop"},{"id":"agent-studio/the-loop-with-a-meter/s03-03-why-did-it-stop"},{"id":"agent-studio/the-loop-with-a-meter/s04-04-predict-the-stop-reason"},{"id":"agent-studio/the-loop-with-a-meter/s05-05-fill-the-budget-check"},{"id":"agent-studio/the-loop-with-a-meter/s06-06-the-trace-is-the-receipt"},{"id":"agent-studio/the-loop-with-a-meter/s07-07-write-run-loop"},{"id":"agent-studio/the-loop-with-a-meter/s08-08-checkpoint"}]},{"slug":"evals-before-it-works","steps":[{"id":"agent-studio/evals-before-it-works/s01-01-green-before-it-runs"},{"id":"agent-studio/evals-before-it-works/s02-02-a-golden-case-is-a-past-incident"},{"id":"agent-studio/evals-before-it-works/s03-03-which-case-catches-it"},{"id":"agent-studio/evals-before-it-works/s04-04-predict-the-eval-run"},{"id":"agent-studio/evals-before-it-works/s05-05-fix-the-router-to-green"},{"id":"agent-studio/evals-before-it-works/s06-06-the-ratchet-entry"},{"id":"agent-studio/evals-before-it-works/s07-07-write-lint-the-ratchet"},{"id":"agent-studio/evals-before-it-works/s08-08-checkpoint"}]}]}]},"detail":{"number":57,"slug":"agent-studio","title":"agent studio — ship one agent feature before you stand up","blurb":"one sitting, one agent feature, end to end: a tool schema that makes the dangerous call a validation error, a loop that meters its own spend, golden cases wired before the router works, a trace you debug from instead of vibes, and the ratchet that turns tonight's incident into tomorrow's eval. practice at production tempo.","overview":"$27","status":"live","lessons":[{"slug":"the-tool-contract","title":"The tool contract — make the dangerous call a validation error","estMinutes":20,"prerequisites":[],"status":"live","steps":[{"type":"read","id":"agent-studio/the-tool-contract/s01-01-the-feature-you-ship-today","xp":1,"hint":[],"personalize":false,"phase":"warmup","estSeconds":170,"concept":"ci-triage-feature-brief","body":"$28","cta":"Got it","runnable":true},{"type":"read","id":"agent-studio/the-tool-contract/s02-02-the-schema-is-the-blast-radius","xp":1,"hint":[],"personalize":false,"phase":"build","estSeconds":200,"concept":"tool-schema-as-data","body":"$29","cta":"Got it","code":"TOOLS = {\n \"get_failing_jobs\": {\"required\": [], \"allowed\": {}, \"confirm\": False},\n \"read_log_tail\": {\"required\": [\"job_id\"], \"allowed\": {}, \"confirm\": False},\n \"open_issue\": {\"required\": [\"title\", \"severity\"],\n \"allowed\": {\"severity\": [\"p1\", \"p2\", \"p3\"]}, \"confirm\": False},\n \"rerun_job\": {\"required\": [\"job_id\"], \"allowed\": {}, \"confirm\": True},\n \"escalate\": {\"required\": [\"oncall\"], \"allowed\": {}, \"confirm\": True},\n}\n\nfor name, spec in TOOLS.items():\n gate = \"CONFIRM\" if spec[\"confirm\"] else \"auto\"\n print(f\"{name:16} required={spec['required']} [{gate}]\")\n","runnable":true},{"type":"mc","id":"agent-studio/the-tool-contract/s03-03-spot-the-loose-tool","xp":2,"hint":[{"level":1,"body":"Ask each spec: what's the worst call that passes validation? For three of them the answer is bounded. For one of them the answer is 'any shell string, unconfirmed.'","cost":0}],"personalize":false,"phase":"build","estSeconds":60,"concept":"loose-tool-spec","prompt":"The agent can call these tools. One of them can break production —\nany shell command, no human thumbprint. Which spec do you block?\n","options":[{"id":"spec_b","label":"B — `run`, no required fields, accepts any shell string, no confirm"},{"id":"spec_a","label":"A — `read_log_tail` with two required fields and no confirm","explain":"Read-only tools don't need confirm — that's the point of splitting reads from writes. Requiring `job_id` and `lines` makes it *narrower*, not looser."},{"id":"spec_c","label":"C — `open_issue` with a severity enum","explain":"This is what a good spec looks like: specific name, required fields, allowed values. Worst case is a noisy issue, and the enum stops even that from being garbage."},{"id":"spec_d","label":"D — `escalate` with confirm required","explain":"Paging a human with confirm: True is exactly the contract you want. The dangerous version of this tool is the one *without* the flag."}],"answerIds":["spec_b"],"shuffle":false,"code":"# four tool specs from four PRs. one of them is a page waiting to happen.\ncandidates = [\n (\"A\", {\"name\": \"read_log_tail\", \"required\": [\"job_id\", \"lines\"],\n \"confirm\": False}),\n (\"B\", {\"name\": \"run\", \"required\": [], \"input\": \"any shell string\",\n \"confirm\": False}),\n (\"C\", {\"name\": \"open_issue\", \"required\": [\"title\", \"severity\"],\n \"allowed\": {\"severity\": [\"p1\", \"p2\", \"p3\"]}, \"confirm\": False}),\n (\"D\", {\"name\": \"escalate\", \"required\": [\"oncall\"], \"confirm\": True}),\n]\nfor tag, spec in candidates:\n print(f\"{tag}: {spec['name']}\")\n","runnable":true},{"type":"predict","id":"agent-studio/the-tool-contract/s04-04-predict-the-validation","xp":3,"hint":[{"level":1,"body":"Call 1 passes everything. Call 2 has both required fields but `p4` isn't in the allowed list — the enum check fires. Call 3 is a valid rerun with no `confirmed` field, so the confirm gate fires. Call 4 is the same call after on-call's approval stamped `confirmed: True`. The tool name is left-aligned (padded with spaces on the right) to width 13.","cost":0},{"level":2,"body":"```\nread_log_tail ok\nopen_issue reject: bad severity\nrerun_job reject: needs confirm\nrerun_job ok\n```\n\nThe model proposed a garbage severity and an unconfirmed rerun in the same run. Neither executed. That's the contract doing its job — the model course-corrects off the error strings, and nothing touched your CI.\n","cost":0}],"personalize":false,"phase":"build","estSeconds":110,"concept":"validator-walkthrough","code":"$2a","prompt":"Four calls hit the validator during one triage run. The model proposed\nthe first three; call 4 is the rejected rerun re-sent after on-call\nclicked approve — the harness stamped `confirmed: True` on it, because\nthat flag comes from a human or an outer policy, never from the model.\nWalk each call through the checks in order (unknown tool → required\nfields → allowed values → confirm) and predict the four output lines.\n\nWatch the second call: the model invented severity `p4`. And note the\nchecks short-circuit — the first failed check names the reject.\n","grader":{"kind":"stdout-equality","expected":"read_log_tail ok\nopen_issue reject: bad severity\nrerun_job reject: needs confirm\nrerun_job ok\n","normalize":"collapse-trailing-newline"}},{"type":"fix","id":"agent-studio/the-tool-contract/s05-05-fix-the-yolo-rerun","xp":4,"hint":[{"level":1,"body":"The validator already checks `spec[\"confirm\"]` — it just never fires because the registry says rerun_job doesn't need confirmation. One boolean, one line. Which tool in this registry can cost money and mask a real failure?","cost":0},{"level":2,"body":"Line 3 becomes:\n\n```python\n\"rerun_job\": {\"required\": [\"job_id\"], \"confirm\": True},\n```\n\n`read_log_tail` stays `False` — it's read-only, and making reads\nrequire confirmation just trains everyone to click through the gate.\n","cost":0}],"personalize":false,"phase":"build","estSeconds":110,"concept":"confirm-flag-on-destructive-tools","brokenCode":"TOOLS = {\n \"read_log_tail\": {\"required\": [\"job_id\"], \"confirm\": False},\n \"rerun_job\": {\"required\": [\"job_id\"], \"confirm\": False},\n}\n\ndef validate_call(call):\n spec = TOOLS[call[\"tool\"]]\n for field in spec[\"required\"]:\n if field not in call[\"args\"]:\n return f\"reject: missing {field}\"\n if spec[\"confirm\"] and not call.get(\"confirmed\"):\n return \"reject: needs confirm\"\n return \"ok\"\n\ncalls = [\n (\"rerun unconfirmed\", {\"tool\": \"rerun_job\", \"args\": {\"job_id\": \"j-118\"}}),\n (\"rerun confirmed \", {\"tool\": \"rerun_job\", \"args\": {\"job_id\": \"j-118\"}, \"confirmed\": True}),\n (\"log read \", {\"tool\": \"read_log_tail\", \"args\": {\"job_id\": \"j-118\"}}),\n]\nfor label, c in calls:\n print(f\"{label} {validate_call(c)}\")\n","prompt":"This tool registry shipped in a Friday PR. Over the weekend the agent\nreran jobs 31 times — including a deploy job, twice — and no confirm\ngate ever fired, because `rerun_job` is registered as if it were\nread-only.\n\nFix the registry so an unconfirmed rerun is rejected. Don't touch the\nvalidator — the bug is in the contract, not the enforcement.\n\nExpected output:\n```\nrerun unconfirmed reject: needs confirm\nrerun confirmed ok\nlog read ok\n```\n","grader":{"kind":"stdout-equality","expected":"rerun unconfirmed reject: needs confirm\nrerun confirmed ok\nlog read ok\n","normalize":"collapse-trailing-newline"},"bugLines":[3],"revealAfter":6},{"type":"write","id":"agent-studio/the-tool-contract/s06-06-write-validate-call","xp":5,"hint":[{"level":1,"body":"Use `TOOLS.get(...)` so an unknown tool returns None instead of raising. Then three loops/checks in the stated order, each returning immediately on failure — the order matters because the second `open_issue` call must reach `ok` while the first stops at `missing severity`. The `escalate` call is valid in every way except the missing `confirmed` field.","cost":0},{"level":2,"body":"```python\ndef validate_call(call):\n spec = TOOLS.get(call[\"tool\"])\n if spec is None:\n return \"reject: unknown tool\"\n for field in spec[\"required\"]:\n if field not in call[\"args\"]:\n return f\"reject: missing {field}\"\n for field, allowed in spec[\"allowed\"].items():\n if call[\"args\"].get(field) not in allowed:\n return f\"reject: bad {field}\"\n if spec[\"confirm\"] and not call.get(\"confirmed\"):\n return \"reject: needs confirm\"\n return \"ok\"\n```\n","cost":0}],"personalize":false,"phase":"build","estSeconds":240,"concept":"write-the-tool-validator","prompt":"Write `validate_call(call)` — the gate every proposed tool call passes\nthrough before anything executes. Checks run in this order, and the\nfirst failure wins:\n\n1. `call[\"tool\"]` not in `TOOLS` → `\"reject: unknown tool\"`\n2. any name in the spec's `required` list missing from `call[\"args\"]`\n → `\"reject: missing \"`\n3. any field in the spec's `allowed` dict whose arg value isn't in the\n allowed list → `\"reject: bad \"`\n4. spec has `confirm: True` and the call lacks a truthy `confirmed`\n → `\"reject: needs confirm\"`\n5. otherwise → `\"ok\"`\n\nExpected output:\n```\nget_failing_jobs ok\nopen_issue reject: missing severity\nopen_issue ok\nescalate reject: needs confirm\ndeploy_prod reject: unknown tool\n```\n","starter":"TOOLS = {\n \"get_failing_jobs\": {\"required\": [], \"allowed\": {}, \"confirm\": False},\n \"read_log_tail\": {\"required\": [\"job_id\"], \"allowed\": {}, \"confirm\": False},\n \"open_issue\": {\"required\": [\"title\", \"severity\"],\n \"allowed\": {\"severity\": [\"p1\", \"p2\", \"p3\"]}, \"confirm\": False},\n \"rerun_job\": {\"required\": [\"job_id\"], \"allowed\": {}, \"confirm\": True},\n \"escalate\": {\"required\": [\"oncall\"], \"allowed\": {}, \"confirm\": True},\n}\n\ncalls = [\n {\"tool\": \"get_failing_jobs\", \"args\": {}},\n {\"tool\": \"open_issue\", \"args\": {\"title\": \"cart test red\"}},\n {\"tool\": \"open_issue\", \"args\": {\"title\": \"cart test red\", \"severity\": \"p2\"}},\n {\"tool\": \"escalate\", \"args\": {\"oncall\": \"infra\"}},\n {\"tool\": \"deploy_prod\", \"args\": {}},\n]\n\n# define validate_call(call) below\n\nfor c in calls:\n print(f\"{c['tool']:16} {validate_call(c)}\")\n","grader":{"kind":"stdout-equality","expected":"get_failing_jobs ok\nopen_issue reject: missing severity\nopen_issue ok\nescalate reject: needs confirm\ndeploy_prod reject: unknown tool\n","normalize":"collapse-trailing-newline"},"solution":"$2b","hiddenTests":[]},{"type":"checkpoint","id":"agent-studio/the-tool-contract/s07-07-checkpoint","xp":8,"hint":[{"level":1,"body":"Reuse your validate_call from the previous step verbatim — the registry gained `escalate` but the rules are identical. `gate_calls` is a loop that builds `{\"tool\": c[\"tool\"], \"verdict\": validate_call(c)}` per call. The traps: `p0` isn't in the severity enum, the unconfirmed rerun hits the confirm gate, and `rm_rf` must return a reject string, not crash.","cost":0},{"level":2,"body":"```python\ndef gate_calls(calls):\n rows = []\n for c in calls:\n rows.append({\"tool\": c[\"tool\"], \"verdict\": validate_call(c)})\n return rows\n```\n\nWith `validate_call` unchanged from the write step. If `rm_rf`\nraises a KeyError, you used `TOOLS[...]` instead of `TOOLS.get(...)`.\n","cost":0}],"personalize":false,"phase":"check","estSeconds":280,"concept":"gate-a-batch-of-calls","prompt":"Checkpoint. It's the end of a triage run and you're auditing the call\nlog. Four of these are what the model proposed; the `escalate` went\nout after on-call approved it — that's where its `confirmed: True`\ncame from, since the model never sets that flag on its own calls.\nWrite `gate_calls(calls)` that returns a list of rows —\none dict `{\"tool\": ..., \"verdict\": ...}` per call, same order — where\n`verdict` comes from `validate_call` (same five rules as the last\nstep: unknown tool, missing required, bad allowed value, needs\nconfirm, ok).\n\nThen print each row, count the verdicts, and end with the summary\nline. Note the model tried to call `rm_rf` — a tool that doesn't\nexist in this registry, which is exactly why \"unknown tool\" is a\nreject and not a KeyError.\n\nExpected output:\n```\nread_log_tail ok\nrerun_job reject: needs confirm\nopen_issue reject: bad severity\nescalate ok\nrm_rf reject: unknown tool\n2 ok / 3 rejected — schema held\n```\n","starter":"TOOLS = {\n \"read_log_tail\": {\"required\": [\"job_id\"], \"allowed\": {}, \"confirm\": False},\n \"open_issue\": {\"required\": [\"title\", \"severity\"],\n \"allowed\": {\"severity\": [\"p1\", \"p2\", \"p3\"]}, \"confirm\": False},\n \"rerun_job\": {\"required\": [\"job_id\"], \"allowed\": {}, \"confirm\": True},\n \"escalate\": {\"required\": [\"oncall\"], \"allowed\": {}, \"confirm\": True},\n}\n\ncalls = [\n {\"tool\": \"read_log_tail\", \"args\": {\"job_id\": \"j-201\"}},\n {\"tool\": \"rerun_job\", \"args\": {\"job_id\": \"j-201\"}},\n {\"tool\": \"open_issue\", \"args\": {\"title\": \"oom on canary\", \"severity\": \"p0\"}},\n {\"tool\": \"escalate\", \"args\": {\"oncall\": \"infra\"}, \"confirmed\": True},\n {\"tool\": \"rm_rf\", \"args\": {\"path\": \"/\"}},\n]\n\n# define validate_call(call) and gate_calls(calls) below\n\nok = 0\nrejected = 0\nfor row in gate_calls(calls):\n print(f\"{row['tool']:14} {row['verdict']}\")\n if row[\"verdict\"] == \"ok\":\n ok += 1\n else:\n rejected += 1\nprint(f\"{ok} ok / {rejected} rejected — schema held\")\n","grader":{"kind":"stdout-equality","expected":"read_log_tail ok\nrerun_job reject: needs confirm\nopen_issue reject: bad severity\nescalate ok\nrm_rf reject: unknown tool\n2 ok / 3 rejected — schema held\n","normalize":"collapse-trailing-newline"},"solution":"$2c","passThreshold":0.66}],"xpTotal":24},{"slug":"the-loop-with-a-meter","title":"The loop with a meter — budget caps, stop reasons, and the trace","estMinutes":23,"prerequisites":[],"status":"live","steps":[{"type":"read","id":"agent-studio/the-loop-with-a-meter/s01-01-a-loop-that-cannot-stop-is-an-invoice","xp":1,"hint":[],"personalize":false,"phase":"warmup","estSeconds":170,"concept":"agent-loop-needs-caps","body":"$2d","cta":"Got it","runnable":true},{"type":"read","id":"agent-studio/the-loop-with-a-meter/s02-02-caps-are-part-of-the-loop","xp":1,"hint":[],"personalize":false,"phase":"warmup","estSeconds":190,"concept":"budget-checks-inside-the-loop","body":"$2e","cta":"Got it","code":"COST = {\"get_failing_jobs\": 0.02, \"read_log_tail\": 0.03,\n \"rerun_job\": 0.11, \"open_issue\": 0.04}\n\nCAPS = {\"max_steps\": 6, \"max_cost_usd\": 0.50}\n\nplan = [\"get_failing_jobs\", \"read_log_tail\", \"rerun_job\", \"open_issue\"]\n\nspent = 0.0\nfor i, tool in enumerate(plan, 1):\n if i > CAPS[\"max_steps\"]:\n print(\"stop: step-cap\")\n break\n if spent + COST[tool] > CAPS[\"max_cost_usd\"]:\n print(\"stop: cost-cap\")\n break\n spent += COST[tool]\n print(f\"step {i}: {tool} ${spent:.2f}\")\nelse:\n print(f\"stop: plan-complete (${spent:.2f} spent)\")\n","runnable":true},{"type":"mc","id":"agent-studio/the-loop-with-a-meter/s03-03-why-did-it-stop","xp":2,"hint":[{"level":1,"body":"Look at the pattern in steps 2-6: read, rerun, read, rerun, read. Same job, no forward progress, and then the stop line names which cap fired. The trace hands you the diagnosis — that's the point of having one.","cost":0}],"personalize":false,"phase":"build","estSeconds":60,"concept":"read-the-stop-reason","prompt":"Caps were `max_steps: 6`, `max_cost_usd: 0.50`. What does this trace\ntell you about the run?\n","options":[{"id":"stuck_loop","label":"The agent got stuck in a read/rerun cycle and the step cap ended the run before it converged"},{"id":"cost_blown","label":"The run was stopped because it exceeded the cost budget","explain":"Read the last line: `stop: step-cap`. Spend was $0.33 of a $0.50 cap — the money was fine. The run died on iterations, which points at a different fix than a cost blowout would."},{"id":"plan_done","label":"The agent finished its triage plan normally","explain":"A normal finish prints `stop: plan-complete`. A run that ends on step-cap never reached a decision — no issue opened, no escalation. That job is still red and nobody was told."},{"id":"validator_fired","label":"The tool contract rejected a call, so the run halted","explain":"Every step in this trace executed and spent money — there's no reject line anywhere. Validation rejects and budget stops are different events, and the trace distinguishes them precisely so you don't have to guess."}],"answerIds":["stuck_loop"],"shuffle":false,"code":"# last night's triage run, straight from the trace\ntrace = [\n \"step 1: get_failing_jobs $0.02\",\n \"step 2: read_log_tail $0.05\",\n \"step 3: rerun_job $0.16\",\n \"step 4: read_log_tail $0.19\",\n \"step 5: rerun_job $0.30\",\n \"step 6: read_log_tail $0.33\",\n \"stop: step-cap\",\n]\nfor line in trace:\n print(line)\n","runnable":true},{"type":"predict","id":"agent-studio/the-loop-with-a-meter/s04-04-predict-the-stop-reason","xp":3,"hint":[{"level":1,"body":"Totals: 0.02, 0.05, 0.08, then the first rerun lands on 0.19. Second rerun: 0.19 + 0.11 = 0.30, and 0.30 > 0.30 is False — exactly-at-cap is allowed, so step 5 runs. Third rerun: 0.30 + 0.11 = 0.41 > 0.30 → the cost gate fires before the tool runs. The plan never reaches open_issue.","cost":0},{"level":2,"body":"```\nstep 1: get_failing_jobs $0.02\nstep 2: read_log_tail $0.05\nstep 3: read_log_tail $0.08\nstep 4: rerun_job $0.19\nstep 5: rerun_job $0.30\nstop: cost-cap before rerun_job ($0.30 spent)\n```\n\nTwo reruns fit the budget; the third is where the meter says no.\nNote what the cap actually bought you: the run stopped at $0.30\nspent, not at $0.41 — the gate fired before the overspending call,\nand the stop line names the tool it refused.\n","cost":0}],"personalize":false,"phase":"build","estSeconds":130,"concept":"trace-the-metered-loop","code":"COST = {\"get_failing_jobs\": 0.02, \"read_log_tail\": 0.03,\n \"rerun_job\": 0.11, \"open_issue\": 0.04}\n\nPLAN = [\"get_failing_jobs\", \"read_log_tail\", \"read_log_tail\",\n \"rerun_job\", \"rerun_job\", \"rerun_job\", \"open_issue\"]\n\nCAPS = {\"max_steps\": 10, \"max_cost_usd\": 0.30}\n\nspent = 0.0\nfor i, tool in enumerate(PLAN, 1):\n if i > CAPS[\"max_steps\"]:\n print(f\"stop: step-cap at step {i}\")\n break\n if spent + COST[tool] > CAPS[\"max_cost_usd\"]:\n print(f\"stop: cost-cap before {tool} (${spent:.2f} spent)\")\n break\n spent += COST[tool]\n print(f\"step {i}: {tool} ${spent:.2f}\")\nelse:\n print(\"stop: plan-complete\")\n","prompt":"A seven-step plan with three reruns in it, a ten-step cap, and a $0.30\nbudget. Walk the loop and predict every line, including the stop line.\n\nKeep a running total, and remember the cost check is `spent + cost >\ncap` — strictly greater — evaluated *before* the spend. The boundary\ncase matters: what happens on the step where spend would land exactly\non $0.30?\n\nAnd remember the `else` from the last read: it runs only if the loop\nnever hits `break`. A run that breaks prints no plan-complete line.\n","grader":{"kind":"stdout-equality","expected":"step 1: get_failing_jobs $0.02\nstep 2: read_log_tail $0.05\nstep 3: read_log_tail $0.08\nstep 4: rerun_job $0.19\nstep 5: rerun_job $0.30\nstop: cost-cap before rerun_job ($0.30 spent)\n","normalize":"collapse-trailing-newline"}},{"type":"fill","id":"agent-studio/the-loop-with-a-meter/s05-05-fill-the-budget-check","xp":3,"hint":[{"level":1,"body":"Three parts: the money already spent, plus the price of the tool about to run, compared against the cap with strict `>`. The prices live in `COST[tool]`, the cap in `CAPS[\"max_cost_usd\"]`.","cost":0},{"level":2,"body":"`spent + COST[tool] > CAPS[\"max_cost_usd\"]` — the would-be total versus the ceiling. If you wrote `spent > CAPS[...]` alone, the check happens one call too late: the budget is already gone by the time it fires.","cost":0}],"personalize":false,"phase":"build","estSeconds":90,"concept":"pre-spend-budget-check","prompt":"The loop below has its cost gate missing. Fill in the condition that\nstops the run *before* a tool call would push spend past the budget —\nask \"would this call bust the cap,\" not \"did the last one.\"\n\nWith the gate in place, the first run prints `cost-cap at $0.14`\n(the second rerun would hit $0.25 against a $0.20 cap) and the second\nprints `plan-complete at $0.06`.\n","code":"COST = {\"read_log_tail\": 0.03, \"rerun_job\": 0.11}\nCAPS = {\"max_steps\": 4, \"max_cost_usd\": 0.20}\n\ndef run(plan):\n spent = 0.0\n for i, tool in enumerate(plan, 1):\n if i > CAPS[\"max_steps\"]:\n return f\"step-cap after {i - 1} steps\"\n if ___:\n return f\"cost-cap at ${spent:.2f}\"\n spent += COST[tool]\n return f\"plan-complete at ${spent:.2f}\"\n\nprint(run([\"read_log_tail\", \"rerun_job\", \"rerun_job\"]))\nprint(run([\"read_log_tail\", \"read_log_tail\"]))\n","blanks":[{"id":"cost_gate","accept":["spent + COST[tool] > CAPS[\"max_cost_usd\"]","spent + COST[tool] > CAPS['max_cost_usd']","spent+COST[tool]>CAPS[\"max_cost_usd\"]","spent+COST[tool]>CAPS['max_cost_usd']","COST[tool] + spent > CAPS[\"max_cost_usd\"]","COST[tool] + spent > CAPS['max_cost_usd']","COST[tool]+spent>CAPS[\"max_cost_usd\"]","COST[tool]+spent>CAPS['max_cost_usd']","spent + COST[tool] > CAPS[\"max_cost_usd\"]:","spent + COST[tool] > CAPS['max_cost_usd']:","spent+COST[tool]>CAPS[\"max_cost_usd\"]:","spent+COST[tool]>CAPS['max_cost_usd']:","COST[tool] + spent > CAPS[\"max_cost_usd\"]:","COST[tool] + spent > CAPS['max_cost_usd']:","COST[tool]+spent>CAPS[\"max_cost_usd\"]:","COST[tool]+spent>CAPS['max_cost_usd']:"],"caseSensitive":true,"normalize":"trim"}]},{"type":"read","id":"agent-studio/the-loop-with-a-meter/s06-06-the-trace-is-the-receipt","xp":1,"hint":[],"personalize":false,"phase":"build","estSeconds":190,"concept":"trace-first-debugging","body":"$2f","cta":"Got it","code":"# one bad run, as their trace records it — this is what you debug from\ntrace = [\n {\"step\": 1, \"tool\": \"get_failing_jobs\", \"verdict\": \"ok\",\n \"result\": \"1 red job: j-118\", \"spent\": 0.02},\n {\"step\": 2, \"tool\": \"read_log_tail\", \"verdict\": \"ok\",\n \"result\": \"npm ERR! 503 registry.npmjs.org\", \"spent\": 0.05},\n {\"step\": 3, \"tool\": \"escalate\", \"verdict\": \"reject: needs confirm\",\n \"result\": None, \"spent\": 0.05},\n {\"step\": 4, \"tool\": \"open_issue\", \"verdict\": \"ok\",\n \"result\": \"issue #4312 (p1)\", \"spent\": 0.09},\n]\n\nfor t in trace:\n flag = \"\" if t[\"verdict\"] == \"ok\" else \" <-- look here\"\n print(f\"step {t['step']}: {t['tool']:16} {t['verdict']}{flag}\")\nprint(f\"total: ${trace[-1]['spent']:.2f}\")\n","runnable":true},{"type":"write","id":"agent-studio/the-loop-with-a-meter/s07-07-write-run-loop","xp":5,"hint":[{"level":1,"body":"Track `spent = 0.0`, iterate with `enumerate(plan, 1)`, and put both cap checks at the top of the loop body — step cap first, then the pre-spend cost check `spent + COST[tool] > caps[\"max_cost_usd\"]`. Format money with `${spent:.2f}`. In run 2, step 4 executes (4 is not > 4) and the cap fires when `i` reaches 5.","cost":0},{"level":2,"body":"```python\ndef run_loop(plan, caps):\n spent = 0.0\n for i, tool in enumerate(plan, 1):\n if i > caps[\"max_steps\"]:\n print(\"stop: step-cap\")\n return\n if spent + COST[tool] > caps[\"max_cost_usd\"]:\n print(f\"stop: cost-cap (${spent:.2f} spent)\")\n return\n spent += COST[tool]\n print(f\"step {i}: {tool} ${spent:.2f}\")\n print(f\"stop: plan-complete (${spent:.2f} spent)\")\n```\n","cost":0}],"personalize":false,"phase":"build","estSeconds":260,"concept":"write-the-metered-loop","prompt":"Write `run_loop(plan, caps)` — the metered loop, as a function you can\npoint at any plan with any budget. Per iteration, in order:\n\n1. If the step number exceeds `caps[\"max_steps\"]` → print\n `stop: step-cap` and return.\n2. If `spent + COST[tool]` exceeds `caps[\"max_cost_usd\"]` (strictly)\n → print `stop: cost-cap ($X.XX spent)` and return.\n3. Otherwise spend, then print `step N: tool $X.XX` with the running\n total.\n\nIf the plan runs out naturally, print\n`stop: plan-complete ($X.XX spent)`.\n\nAll money is `$` + two decimals. Three runs exercise all three exits:\n\n```\nstep 1: get_failing_jobs $0.02\nstep 2: read_log_tail $0.05\nstep 3: open_issue $0.09\nstop: plan-complete ($0.09 spent)\nstep 1: get_failing_jobs $0.02\nstep 2: rerun_job $0.13\nstep 3: rerun_job $0.24\nstep 4: rerun_job $0.35\nstop: step-cap\nstep 1: rerun_job $0.11\nstep 2: rerun_job $0.22\nstop: cost-cap ($0.22 spent)\n```\n","starter":"COST = {\"get_failing_jobs\": 0.02, \"read_log_tail\": 0.03,\n \"rerun_job\": 0.11, \"open_issue\": 0.04}\n\n# define run_loop(plan, caps) below\n\nrun_loop([\"get_failing_jobs\", \"read_log_tail\", \"open_issue\"],\n {\"max_steps\": 6, \"max_cost_usd\": 0.50})\nrun_loop([\"get_failing_jobs\"] + [\"rerun_job\"] * 5,\n {\"max_steps\": 4, \"max_cost_usd\": 1.00})\nrun_loop([\"rerun_job\", \"rerun_job\", \"rerun_job\"],\n {\"max_steps\": 6, \"max_cost_usd\": 0.25})\n","grader":{"kind":"stdout-equality","expected":"step 1: get_failing_jobs $0.02\nstep 2: read_log_tail $0.05\nstep 3: open_issue $0.09\nstop: plan-complete ($0.09 spent)\nstep 1: get_failing_jobs $0.02\nstep 2: rerun_job $0.13\nstep 3: rerun_job $0.24\nstep 4: rerun_job $0.35\nstop: step-cap\nstep 1: rerun_job $0.11\nstep 2: rerun_job $0.22\nstop: cost-cap ($0.22 spent)\n","normalize":"collapse-trailing-newline"},"solution":"COST = {\"get_failing_jobs\": 0.02, \"read_log_tail\": 0.03,\n \"rerun_job\": 0.11, \"open_issue\": 0.04}\n\ndef run_loop(plan, caps):\n spent = 0.0\n for i, tool in enumerate(plan, 1):\n if i > caps[\"max_steps\"]:\n print(\"stop: step-cap\")\n return\n if spent + COST[tool] > caps[\"max_cost_usd\"]:\n print(f\"stop: cost-cap (${spent:.2f} spent)\")\n return\n spent += COST[tool]\n print(f\"step {i}: {tool} ${spent:.2f}\")\n print(f\"stop: plan-complete (${spent:.2f} spent)\")\n\nrun_loop([\"get_failing_jobs\", \"read_log_tail\", \"open_issue\"],\n {\"max_steps\": 6, \"max_cost_usd\": 0.50})\nrun_loop([\"get_failing_jobs\"] + [\"rerun_job\"] * 5,\n {\"max_steps\": 4, \"max_cost_usd\": 1.00})\nrun_loop([\"rerun_job\", \"rerun_job\", \"rerun_job\"],\n {\"max_steps\": 6, \"max_cost_usd\": 0.25})\n","hiddenTests":[]},{"type":"checkpoint","id":"agent-studio/the-loop-with-a-meter/s08-08-checkpoint","xp":8,"hint":[{"level":1,"body":"The one design decision that trips people: a rejected call uses `continue`, not `return` — the run goes on, the step counter advances, and `spent` doesn't move. So in run 1 the unconfirmed rerun is step 2 at $0.03, and the confirmed rerun is step 3 landing at $0.14. Order inside the loop: step cap, then validation, then the pre-spend cost gate.","cost":0},{"level":2,"body":"```python\ndef triage_run(plan, caps):\n spent = 0.0\n for i, call in enumerate(plan, 1):\n if i > caps[\"max_steps\"]:\n print(f\"stop: step-cap (${spent:.2f} spent)\")\n return\n spec = TOOLS[call[\"tool\"]]\n if spec[\"confirm\"] and not call.get(\"confirmed\"):\n print(f\"step {i}: {call['tool']} reject: needs confirm\")\n continue\n if spent + spec[\"cost\"] > caps[\"max_cost_usd\"]:\n print(f\"stop: cost-cap (${spent:.2f} spent)\")\n return\n spent += spec[\"cost\"]\n print(f\"step {i}: {call['tool']} ok ${spent:.2f}\")\n print(f\"stop: plan-complete (${spent:.2f} spent)\")\n```\n","cost":0}],"personalize":false,"phase":"check","estSeconds":290,"concept":"validated-metered-loop","prompt":"$30","starter":"TOOLS = {\n \"read_log_tail\": {\"confirm\": False, \"cost\": 0.03},\n \"rerun_job\": {\"confirm\": True, \"cost\": 0.11},\n \"open_issue\": {\"confirm\": False, \"cost\": 0.04},\n}\n\n# define triage_run(plan, caps) below\n\ntriage_run(\n [\n {\"tool\": \"read_log_tail\"},\n {\"tool\": \"rerun_job\"},\n {\"tool\": \"rerun_job\", \"confirmed\": True},\n {\"tool\": \"open_issue\"},\n ],\n {\"max_steps\": 6, \"max_cost_usd\": 0.50},\n)\ntriage_run(\n [\n {\"tool\": \"rerun_job\", \"confirmed\": True},\n {\"tool\": \"rerun_job\", \"confirmed\": True},\n {\"tool\": \"rerun_job\", \"confirmed\": True},\n ],\n {\"max_steps\": 6, \"max_cost_usd\": 0.25},\n)\n","grader":{"kind":"stdout-equality","expected":"step 1: read_log_tail ok $0.03\nstep 2: rerun_job reject: needs confirm\nstep 3: rerun_job ok $0.14\nstep 4: open_issue ok $0.18\nstop: plan-complete ($0.18 spent)\nstep 1: rerun_job ok $0.11\nstep 2: rerun_job ok $0.22\nstop: cost-cap ($0.22 spent)\n","normalize":"collapse-trailing-newline"},"solution":"$31","passThreshold":0.66}],"xpTotal":24},{"slug":"evals-before-it-works","title":"Evals before it works — golden cases and the ratchet","estMinutes":23,"prerequisites":[],"status":"live","steps":[{"type":"read","id":"agent-studio/evals-before-it-works/s01-01-green-before-it-runs","xp":1,"hint":[],"personalize":false,"phase":"warmup","estSeconds":180,"concept":"evals-before-feature-done","body":"$32","cta":"Got it","runnable":true},{"type":"read","id":"agent-studio/evals-before-it-works/s02-02-a-golden-case-is-a-past-incident","xp":1,"hint":[],"personalize":false,"phase":"warmup","estSeconds":180,"concept":"golden-case-anatomy","body":"$33","cta":"Got it","code":"# the triage agent's golden set — every case is a real past incident\nGOLDEN = [\n (\"G1\", \"unit test timeout on runner 3\", \"rerun\"),\n (\"G2\", \"prod deploy failed healthcheck\", \"escalate\"),\n (\"G3\", \"assertion error in cart total\", \"open_issue\"),\n (\"G4\", \"npm registry 503 during install\", \"rerun\"),\n]\n\nFORBIDDEN = {\n # route that must NEVER happen for this case, incident that taught us\n \"G2\": (\"open_issue\", \"2026-06-30: prod down 40min, p3 filed, nobody paged\"),\n \"G4\": (\"escalate\", \"2026-07-08: on-call paged at 2am for a registry blip\"),\n}\n\nfor cid, job, want in GOLDEN:\n print(f\"{cid}: '{job}' -> {want}\")\nfor cid, (never, incident) in FORBIDDEN.items():\n print(f\"{cid} must never -> {never} ({incident})\")\n","runnable":true},{"type":"mc","id":"agent-studio/evals-before-it-works/s03-03-which-case-catches-it","xp":2,"hint":[{"level":1,"body":"Run the incident text through the router in your head: '503' matches neither 'prod', 'timeout', nor 'connection reset', so it falls through to open_issue. The catching case is the one whose input takes that exact fall-through path but whose expected answer is rerun.","cost":0}],"personalize":false,"phase":"build","estSeconds":60,"concept":"case-per-failure-mode","prompt":"Incident, week two: the npm registry had an outage, forty builds went\nred with `npm ERR! 503`, and the agent opened forty issues instead of\nrerunning. The team wants a golden case that would have caught this\n*before* ship. Which case does the job?\n","options":[{"id":"case_503","label":"(\"G4\", \"npm registry 503 during install\", \"rerun\")"},{"id":"case_timeout","label":"(\"G1\", \"unit test timeout on runner 3\", \"rerun\")","explain":"This case already passes — 'timeout' matches a keyword the router has. A case the router already handles can't catch the mode it's missing. The whole incident happened because a 503 looks nothing like a timeout."},{"id":"case_prod","label":"(\"G2\", \"prod deploy failed healthcheck\", \"escalate\")","explain":"Also already green — 'prod' hits the escalate branch. Good case to keep, wrong case for this incident: it exercises the escalation mode, not the flake-detection hole."},{"id":"case_forty","label":"Forty cases, one per red build from the outage","explain":"All forty are the same failure mode with the same fix. One case per mode is the rule — forty copies add runtime and review noise without adding one bit of new coverage."}],"answerIds":["case_503"],"shuffle":false,"code":"def route(job):\n text = job.lower()\n if \"prod\" in text or \"security\" in text:\n return \"escalate\"\n if \"timeout\" in text or \"connection reset\" in text:\n return \"rerun\"\n return \"open_issue\"\n\nprint(\"router loaded — keyword rules: prod/security, timeout/connection reset\")\n","runnable":true},{"type":"predict","id":"agent-studio/evals-before-it-works/s04-04-predict-the-eval-run","xp":3,"hint":[{"level":1,"body":"G1 hits 'timeout' → rerun, pass. G2 hits 'prod' → escalate, pass. G3 matches no keyword → open_issue, pass (that IS the right route for a real assertion failure). G4: '503' matches nothing, falls through to open_issue — but the incident says a registry 503 is a flake. One FAIL means the summary condition fails.","cost":0},{"level":2,"body":"```\nG1 pass (got rerun)\nG2 pass (got escalate)\nG3 pass (got open_issue)\nG4 FAIL (got open_issue)\n3/4 — hold\n```\n\nThe router looked done — it handled every case its author remembered.\nThe golden set remembered one more. That gap between \"looks done\"\nand \"passes the incidents\" is exactly what wiring evals first buys\nyou: you found this at your desk, not in the issue tracker.\n","cost":0}],"personalize":false,"phase":"build","estSeconds":120,"concept":"run-the-golden-set","code":"def route(job):\n text = job.lower()\n if \"prod\" in text or \"security\" in text:\n return \"escalate\"\n if \"timeout\" in text or \"connection reset\" in text:\n return \"rerun\"\n return \"open_issue\"\n\nGOLDEN = [\n (\"G1\", \"unit test timeout on runner 3\", \"rerun\"),\n (\"G2\", \"prod deploy failed healthcheck\", \"escalate\"),\n (\"G3\", \"assertion error in cart total\", \"open_issue\"),\n (\"G4\", \"npm registry 503 during install\", \"rerun\"),\n]\n\npassed = 0\nfor cid, job, want in GOLDEN:\n got = route(job)\n ok = got == want\n passed += ok\n print(f\"{cid} {'pass' if ok else 'FAIL'} (got {got})\")\nprint(f\"{passed}/{len(GOLDEN)} — {'ship' if passed == len(GOLDEN) else 'hold'}\")\n","prompt":"The router was written from memory of recent flakes: prod escalates,\ntimeouts rerun. The golden set holds four real incidents. Run each\ncase through `route` and predict the output — four case lines, then\nthe summary.\n\n(`passed += ok` adds a boolean: True is 1, False is 0.)\n","grader":{"kind":"stdout-equality","expected":"G1 pass (got rerun)\nG2 pass (got escalate)\nG3 pass (got open_issue)\nG4 FAIL (got open_issue)\n3/4 — hold\n","normalize":"collapse-trailing-newline"}},{"type":"fix","id":"agent-studio/evals-before-it-works/s05-05-fix-the-router-to-green","xp":4,"hint":[{"level":1,"body":"One condition needs one more clause: the rerun branch should also fire when the job text contains \"503\". Do NOT touch GOLDEN — editing the expected answer to match the broken router is the eval-set crime this whole lesson exists to prevent.","cost":0},{"level":2,"body":"Line 5 becomes:\n\n```python\nif \"timeout\" in text or \"connection reset\" in text or \"503\" in text:\n```\n\nKeep the prod check above it — order matters. A hypothetical\n\"prod deploy timeout\" must still escalate, which it does because\nthe escalate branch runs first.\n","cost":0}],"personalize":false,"phase":"build","estSeconds":120,"concept":"red-to-green-on-golden-cases","brokenCode":"def route(job):\n text = job.lower()\n if \"prod\" in text or \"security\" in text:\n return \"escalate\"\n if \"timeout\" in text or \"connection reset\" in text:\n return \"rerun\"\n return \"open_issue\"\n\nGOLDEN = [\n (\"G1\", \"unit test timeout on runner 3\", \"rerun\"),\n (\"G2\", \"prod deploy failed healthcheck\", \"escalate\"),\n (\"G3\", \"assertion error in cart total\", \"open_issue\"),\n (\"G4\", \"npm registry 503 during install\", \"rerun\"),\n]\n\npassed = 0\nfor cid, job, want in GOLDEN:\n got = route(job)\n ok = got == want\n passed += ok\n print(f\"{cid} {'pass' if ok else 'FAIL'} (got {got})\")\nprint(f\"{passed}/{len(GOLDEN)} — {'ship' if passed == len(GOLDEN) else 'hold'}\")\n","prompt":"Same router, same golden set, same red run: `G4 FAIL`, `3/4 — hold`.\nNow do the TDD move — change the *router* until the run is green. The\ngolden set is the spec; it doesn't move.\n\nA registry 503 is transient infrastructure noise, same class as a\ntimeout: the flake branch needs to recognize it.\n\nExpected output:\n```\nG1 pass (got rerun)\nG2 pass (got escalate)\nG3 pass (got open_issue)\nG4 pass (got rerun)\n4/4 — ship\n```\n","grader":{"kind":"stdout-equality","expected":"G1 pass (got rerun)\nG2 pass (got escalate)\nG3 pass (got open_issue)\nG4 pass (got rerun)\n4/4 — ship\n","normalize":"collapse-trailing-newline"},"bugLines":[5],"revealAfter":6},{"type":"read","id":"agent-studio/evals-before-it-works/s06-06-the-ratchet-entry","xp":1,"hint":[],"personalize":false,"phase":"build","estSeconds":190,"concept":"ratchet-five-fields","body":"$34","cta":"Got it","code":"# the ratchet log, day 21 of the triage agent\nRATCHET = [\n {\"date\": \"2026-07-14\",\n \"failure\": \"agent reran j-118 four times on one red build, $0.44 burned\",\n \"rule\": \"rerun_job max once per job per run; second red -> open_issue\",\n \"artifact\": \"AGENTS.md line 31 + cost cap in triage_run\",\n \"remove_when\": \"provider ships native per-tool rate limits\"},\n {\"date\": \"2026-07-19\",\n \"failure\": \"npm 503 outage: 40 issues opened, zero reruns\",\n \"rule\": \"'503' in job text routes to rerun\",\n \"artifact\": \"route() flake branch + golden case G4\",\n \"remove_when\": \"flake classifier replaces keyword routing (eval >= 95%)\"},\n]\n\nfor i, e in enumerate(RATCHET, 1):\n print(f\"R{i} [{e['date']}] {e['rule']}\")\n print(f\" earned by: {e['failure']}\")\n","runnable":true},{"type":"write","id":"agent-studio/evals-before-it-works/s07-07-write-lint-the-ratchet","xp":5,"hint":[{"level":1,"body":"Loop a tuple of the five field names in order and check `not entry.get(field)` — that one expression covers both missing keys and empty strings, since `.get` returns None for absent keys and `''` is falsy. R2's `remove_when` is `\"\"`, which is why it rejects. The vibes check is `\"be careful\" in entry[\"rule\"].lower()`, and it runs only after all five fields pass.","cost":0},{"level":2,"body":"```python\ndef lint_entry(entry):\n for field in (\"date\", \"failure\", \"rule\", \"artifact\", \"remove_when\"):\n if not entry.get(field):\n return f\"reject: missing {field}\"\n if \"be careful\" in entry[\"rule\"].lower():\n return \"reject: vibes rule\"\n return \"ok\"\n```\n\nR2 documents a real failure and a real fix — and still rejects,\nbecause a rule with no exit condition is permanent, and permanent\nrules are debt. The lint forces the author to write the exit now.\n","cost":0}],"personalize":false,"phase":"build","estSeconds":240,"concept":"lint-ratchet-entries","prompt":"Three ratchet entries landed in one PR after a rough on-call week.\nWrite `lint_entry(entry)` — the reviewer that holds every entry to\nthe five-field standard before it's merged:\n\n1. Each of the five fields — `date`, `failure`, `rule`, `artifact`,\n `remove_when` — must be present *and* non-empty. First missing or\n empty one (in that order) → `\"reject: missing \"`.\n2. If the rule contains `\"be careful\"` (any casing) →\n `\"reject: vibes rule\"`. Rules are actions with concrete strings,\n not adjectives.\n3. Otherwise → `\"ok\"`.\n\nPrint one line per entry, then the summary count.\n\nExpected output:\n```\nR1 ok\nR2 reject: missing remove_when\nR3 reject: vibes rule\n1/3 entries earned their line\n```\n","starter":"$35","grader":{"kind":"stdout-equality","expected":"R1 ok\nR2 reject: missing remove_when\nR3 reject: vibes rule\n1/3 entries earned their line\n","normalize":"collapse-trailing-newline"},"solution":"$36","hiddenTests":[]},{"type":"checkpoint","id":"agent-studio/evals-before-it-works/s08-08-checkpoint","xp":8,"hint":[{"level":1,"body":"ship_gate is the eval loop from the predict step with a three-way verdict per case: pass; `FAIL (forbidden: )` when `got == FORBIDDEN.get(cid)`; plain `FAIL` otherwise. Use `.get` — cases without a forbidden route return None, and None never equals a route string. After the first run, append the G5 tuple, set `FORBIDDEN[\"G5\"] = \"open_issue\"`, and call the gate again. G5 fails because 'disk full' matches no keyword and falls through to open_issue — the exact route the incident forbids.","cost":0},{"level":2,"body":"```python\ndef ship_gate(golden):\n passed = 0\n for cid, job, want in golden:\n got = route(job)\n ok = got == want\n passed += ok\n if ok:\n print(f\"{cid} pass\")\n elif got == FORBIDDEN.get(cid):\n print(f\"{cid} FAIL (forbidden: {got})\")\n else:\n print(f\"{cid} FAIL\")\n if passed == len(golden):\n print(f\"{passed}/{len(golden)} SHIP\")\n else:\n print(f\"{passed}/{len(golden)} HOLD ({len(golden) - passed} failing)\")\n\nship_gate(GOLDEN)\nGOLDEN.append((\"G5\", \"runner disk full for the third day\", \"escalate\"))\nFORBIDDEN[\"G5\"] = \"open_issue\"\nship_gate(GOLDEN)\n```\n\nThat HOLD is the feature working — and the `(forbidden: open_issue)`\ntag is the eval telling you this isn't just a miss, it's a repeat\nof the incident. The next moves are lesson 3's routine: fix the\nrouter, watch G5 go green, append the ratchet entry. The gate is\nstronger tonight than it was this morning — that's the whole\nstudio in two eval runs.\n","cost":0}],"personalize":false,"phase":"check","estSeconds":290,"concept":"ship-gate-and-growing-set","prompt":"$37","starter":"def route(job):\n text = job.lower()\n if \"prod\" in text or \"security\" in text:\n return \"escalate\"\n if \"timeout\" in text or \"connection reset\" in text or \"503\" in text:\n return \"rerun\"\n return \"open_issue\"\n\nGOLDEN = [\n (\"G1\", \"unit test timeout on runner 3\", \"rerun\"),\n (\"G2\", \"prod deploy failed healthcheck\", \"escalate\"),\n (\"G3\", \"assertion error in cart total\", \"open_issue\"),\n (\"G4\", \"npm registry 503 during install\", \"rerun\"),\n]\n\nFORBIDDEN = {\n # route that must NEVER fire for this case — each line earned by an incident\n \"G2\": \"open_issue\",\n \"G4\": \"escalate\",\n}\n\n# define ship_gate(golden) below, then:\n# 1. run it on GOLDEN\n# 2. append the G5 incident case and record its forbidden route\n# 3. run it again\n","grader":{"kind":"stdout-equality","expected":"G1 pass\nG2 pass\nG3 pass\nG4 pass\n4/4 SHIP\nG1 pass\nG2 pass\nG3 pass\nG4 pass\nG5 FAIL (forbidden: open_issue)\n4/5 HOLD (1 failing)\n","normalize":"collapse-trailing-newline"},"solution":"$38","passThreshold":0.66}],"xpTotal":25}],"liveLessonCount":3,"liveStepCount":23,"xpTotal":73}},"chapter":"$1c:2:props:tree:detail","lesson":"$1c:2:props:tree:detail:lessons:1","step":"$1c:2:props:tree:detail:lessons:1:steps:2","stepIndex":2,"nav":{"tocNext":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"tocPrev":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"nextByPath":{"developer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"marketer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"designer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"customer-service":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"copywriter":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"data-analyst":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"project-manager":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"hr-specialist":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"operations":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3},"lawyer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":3}},"prevByPath":{"developer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"marketer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"designer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"customer-service":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"copywriter":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"data-analyst":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"project-manager":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"hr-specialist":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"operations":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1},"lawyer":{"chapterSlug":"agent-studio","lessonSlug":"the-loop-with-a-meter","stepIndex":1}}}}]]

The loop with a meter — budget caps, stop reasons, and the trace — step 3 of 8