engineer-agent-loop

engineer-agent-loop

The model is a fraction of a working agent; the loop around it does the rest. This skill designs that loop — or diagnoses one that stalls, repeats, drifts, or never stops — by putting control flow in code: bounded, externally verified, recoverable. Most agent failures are stopping-problem failures, and they are silent — no exception marks a loop that is busy going nowhere.

When NOT to use

• The goal text is the problem (unverifiable condition, gameable done-state) → write-agent-goal. Identify the owning layer from evidence, not symptom alone: premature "done" can be a verifier bug (runtime) just as a vague goal can loop forever (text). Goal wording problems → there; missing caps, weak verifiers, broken recovery → here.
• Prompt wording → optimize-prompt. Comparing prompt variants → evaluate-prompts.
• Ordinary programming loops — an infinite for loop or non-terminating recursion is a code bug, not loop engineering.
• Scheduling — running something every N minutes is cron/interval-runner territory, not loop design.
• Compound asks ("fix the goal AND cap the loop"): sequence them — goal text via write-agent-goal, enforcement here.

Workflow

1. Pick the shape by path-knowability. Path unknown → ReAct; knowable and auditable → plan-and-execute with a replanner; fixed steps → hardcoded pipeline, no agent. Escalate to multi-agent only on an observed failure (context pressure, serial-latency wall, genuine heterogeneity) — and price it. Selection table and recipes: references/loop-patterns.md.
2. Make termination supervisor-owned. Never let the model own stopping. Layer independent caps in code: iteration cap, wall-clock timeout, token/cost budget, cycle detection. Bounds must be effective — cumulative and session-wide; a local retry cap that an outer workflow re-enters bounds nothing. Define explicit terminal states — SUCCESS / FAILED / BUDGET_EXHAUSTED / CANCELLED — each reachable, each reported, with cancellation that works mid-run. Map every cap to a terminal reason (a wall-clock timeout is a reported TIMED_OUT/FAILED, never a silent exit); pre-flight budget checks must reserve worst-case output and in-flight concurrent spend; cancellation must also clean up still-running tool calls.
3. Detect no-progress deterministically — and state-aware. Compare normalized tool calls against a task-state fingerprint: a repeated cycle with no state change is a loop; legitimate polling (results change) and a single backtrack are not. Tunable defaults: identical call 3× → exit with diagnostic; catch A→B→A oscillation; watch tokens climbing while state doesn't move; 3 failed fix attempts → escalate to a human. No LLM judge needed: references/reliability.md.
4. Gate exits on external verification. Maker–checker split with a fresh-context verifier, framed adversarially ("try to disprove"); the verifier checks criteria only — never "verify and improve". A model verifier is a decorrelated probabilistic check, not proof — deterministic checks run first and remain the gate of record; evaluate the trajectory, not just the final answer.
5. Budget the context like RAM. Target ~60–75% utilization (practitioner default — tune); compact at semantic boundaries with a pre-compaction flush to a state file; evict acted-on tool output instead of summarizing it; trim the tool registry. Full discipline: references/context-budget.md.
6. Make it crash-safe. State files are the system of record for local artifacts — reconstruct from git log + progress file, never chat history. External side effects need more: write the intent record before acting and reconcile on resume (a crash between a side effect and its checkpoint is an unknown outcome), fence concurrent resumed supervisors with leases, and put idempotency keys on every side-effecting call — enforced receiver-side or in a durable dedup layer; the key alone is a request, not a guarantee. Budget breach = checkpoint with partial work preserved, not a cliff.
7. Test the loop before trusting it. Run it against: a mocked model that always wants another iteration; a verifier that always rejects; a verifier that hangs; budget exhaustion at exact boundaries; kill-and-restart mid-run; forced compaction immediately before completion. Supervisor caps must hold against every one of them.

Output spec

For a design: pattern + rationale, a cap table with concrete values, terminal states, verifier gates, the context plan, and the recovery plan — plus the step-7 test list for anything that will run unattended. For a diagnosis: the failure family, the trace evidence, the specific missing control, and the fix. $ARGUMENTS, when present, is the loop or symptom to work on.

Gotchas

• Prompt-level caps are advisory: ~38% of confirmed infinite agentic loops had model-controlled stop conditions (arxiv.org/abs/2607.01641).
• A correct-looking final answer can sit on top of wrong state — trajectory evaluation catches what final-answer checks miss.
• Reflection without an external verifier rubber-stamps its own work; cap reflection rounds — the gains land in the first one or two.
• Multi-agent wins are real and expensive: the oft-quoted 90.2% improvement was one internal Anthropic eval and cost ~15x the tokens. Quote the scope and the cost with the win.
• Everything the loop reads — repo files, tool output, retrieved pages — is untrusted input to both maker and verifier; injection can subvert an LLM checker. Least-privilege tool scopes, sandboxed side effects, human approval for irreversible actions, and secrets kept out of traces and state files are part of the loop design, not extras.
• Per-step reliability compounds: 0.95^20 ≈ 36% (arithmetic, not a provider stat) — shorten chains and verify per step.
• Compaction silently drops exact numbers, negations, and ruled-out approaches — use a fixed summary schema and flush state before compacting.

Pointers

• references/loop-patterns.md — pattern selection, canonical citations, plan-and-execute recipe, reflection discipline, multi-agent criteria, the Ralph prior art and its critique.
• references/reliability.md — caps in code, effective bounds, budget mechanics, no-progress detection, hooks and idempotency, verification gates, compounding math, incidents-to-regression-tests.
• references/context-budget.md — window-as-RAM, the four levers with correct attribution, eviction, compaction discipline, external state, version-gated platform facts.