Your agent said "done". Production disagreed.
If you run autonomous coding agents (Cursor, Claude Code, Windsurf, custom loops), you have met the silent failure mode: the agent returns plausible output, the pipeline accepts it, and the breakage surfaces three steps downstream.
The fix is not a smarter model. It is deterministic contracts at every handoff. Below are the 5 JSON Schemas I now require in every agent pipeline.
1. Task Handoff Schema
Every task between agents carries: id, goal, inputs[], acceptance_criteria[], max_turns. If an agent cannot produce acceptance_criteria, it is not allowed to start.
2. Tool-Call Envelope
Wrap every tool call as {tool, args, expected_shape, on_failure}. expected_shape is validated before the result re-enters the agent context, so a malformed API response never poisons reasoning.
3. Code-Evaluation Result
{status: pass|fail, tests_run, tests_passed, error_excerpt}. No free-text "looks good". A pipeline that cannot count tests cannot trust a claim.
4. Review Verdict
{verdict: approve|request_changes, blocking_issues[], nits[]}. Splitting blocking from non-blocking stops the classic loop where an agent blocks a PR over a typo.
5. Artifact Manifest
{files[], hash, produced_by, verified_by}. Determinism lives here: if the hash is not in the manifest, it did not ship.
Why this works
Schemas move failure detection left — from a 2 a.m. incident to a validation error at the boundary. They are boring, versionable, and model-agnostic: swap GPT for Claude and the contracts still hold.
I packaged these 5 schemas (plus a Pydantic V2 validation CLI and cross-platform configs for Cursor/Windsurf/Claude Code) into a drop-in vault:
-> Universal Agent Skills & Production Prompt Vault 2026 — 50% OFF with code LAUNCH50
https://ancuboy.gumroad.com/l/universal-agent-skills-vault/LAUNCH50
Deploy contracts that hold. Stop fixing broken agent runs by hand.
Built by a solo engineer shipping deterministic automation tools.
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