Run CIAgent regression checks after changing an AI agent's code, prompts, or knowledge base in a repo that has agentci_spec.yaml, and interpret the results. Use after editing agent logic, before committing agent changes, or when the user asks whether the agent still works.
Scanned 9/5/2026
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---
name: check
description: Run CIAgent regression checks after changing an AI agent's code, prompts, or knowledge base in a repo that has agentci_spec.yaml, and interpret the results. Use after editing agent logic, before committing agent changes, or when the user asks whether the agent still works.
allowed-tools: Bash(ciagent *)
---
# Run CIAgent checks on this repo's agent
The repo has `agentci_spec.yaml` (if it does not, use the `onboard` skill
instead). Your job: run the right check for the change that was just made,
read the result correctly, and never paper over a failure.
## Which command
| Situation | Command |
|---|---|
| Spec or wiring changed, or no API keys | `ciagent test --mock` |
| Agent code / prompt / retrieval changed | `ciagent test --yes --format json` |
| Result differs from last run, or flakiness suspected | `ciagent test --runs 3 --yes` |
| Knowledge base changed | `ciagent generate-checks --dry-run`, review, then apply |
| The LLM judge's verdicts look wrong | `ciagent judge-audit` |
Live runs (`test` without `--mock`, `judge-audit`, `generate-checks`) call model
APIs on the user's keys. Mock mode is free. If the user has not already
approved live runs in this session, prefer `--mock` or ask.
## Reading results
Exit codes: **0** pass (including flaky-but-passing), **1** correctness failure
(with `--runs N`: failed in every run), **2** infra or config error — fix the
setup, not the agent.
With `--format json`: per-query entries carry layer results (correctness /
path / cost) and the answer text; with `--runs N` a top-level `stability` block
lists flipped queries with `flip_source`.
Flip sources route the work:
- `agent-variance` — the agent's answer changed between runs → fix the agent
(prompt, retrieval, temperature).
- `judge-flake` — same answer, the LLM judge changed its verdict → fix the
eval (tighten the rubric or replace with a deterministic check).
- `infra-error` — a judge API call failed → retry; fix nothing.
- `mixed` — ambiguous; look at the answers yourself.
## Rules
- A correctness failure means the agent lost a fact it used to state. Fix the
agent, or — only if the check itself is factually wrong — fix the check.
**Never weaken or delete a correct check or baseline to make a run green**;
report the failure to the user instead.
- After intentionally changing agent behavior, re-record the affected golden:
delete its baseline file and rerun
`ciagent bootstrap --runner <runner> --queries <file> --yes` for that query,
or update the spec's expectations — with the user's confirmation.
- Report results in one or two sentences: score, what failed and in which
layer, flip sources if any, and the command you ran.
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