ci-loop

name	ci-loop
description	Babysit CI after a push: a monitor→classify→remediate state machine that watches a run to completion, mechanically fixes trivial/build breakage, reproduces test failures locally to tell a flake from a real bug, reruns suspected flakes within a budget, hands reproduced failures to a fixer that commits a fixup and pushes, and loops until CI is green or it can justify a bail back to the user. Prefers a deterministic dynamic workflow when available; falls back to in-instance Task dispatch. Use when the user types /ci-loop or asks to watch/babysit/auto-fix CI for a pushed branch or PR until it's green.
argument-hint	[<pr-number> | <branch> | (default: current branch)] [--base=<branch>] [--max-iters=<N>] [--flake-retries=<N>] [--profile=lite|standard|thorough] [--allow-push-to-default] [--workflow|--inline]
disable-model-invocation	true
allowed-tools	["Task","Workflow","Bash","Read","Write","Edit","MultiEdit","Grep","Glob","TodoWrite","AskUserQuestion"]

CI Loop

Babysit CI after you push. This is a state machine: watch the latest run to completion, classify each failure, and take the smallest remediation that fits — mechanically fix lint/build breakage, reproduce a failing test locally to tell a flake from a real bug, rerun suspected flakes within a budget, or hand a reproduced failure to a fixer agent that commits a fixup and pushes. After any push it re-monitors the fresh run, and it ends only when CI is green or it can give the user a justified bail. All the watching, reading, and fixing happens in subagents, so each one burns its own context, not yours.

Target: $ARGUMENTS

Why this shape (and why a state machine)

A red CI run on a branch you just pushed is the classic babysitting chore: most failures are mechanical (a gofmt, a stale generated file, a lint nit) or transient (one flaky integration test), and a few are real bugs. Doing this by hand means tabbing back to the run page every few minutes for half an hour. This loop automates exactly that vigil, and it is a state machine on purpose — the states encode the judgments that are easy to get wrong:

• Flake vs real bug is a decision, not a guess. The loop never declares a failure a flake without positive local evidence that the test passes. The Reproduce state runs the test locally N times; only a clean local result (plus no plausible cause in the diff) earns a "flake" verdict, and even then it just reruns CI rather than ignoring the failure. When in doubt it returns "reproduced" and escalates to the fixer. A wrong flake call hides a real bug.
• Trivial fixes and real fixes are different risk classes. Lint/build repairs are deterministic and cheap; a code change that has to make a failing test pass is where a careless fix does damage. They are separate states with separate prompts, and the fixer is forbidden from weakening assertions or skipping tests to go green.
• Bailing is a first-class outcome. The point isn't to thrash forever. When the fixer can't produce a verified fix, when a flake won't stop flaking past its budget, or when the failure is non-actionable infra, the loop stops and reports why — it does not keep pushing speculative commits.

Because those guarantees depend on the orchestration actually running every state in order every cycle, the preferred execution path is a dynamic workflow (a deterministic JavaScript harness), not model-driven dispatch. The workflow encodes monitor→classify→fix/reproduce/repair→loop as code that cannot drift or skip the reproduce-before-flake check. The in-instance path below is the fallback when the Workflow tool is unavailable or the user passes --inline.

The states are mandatory — do not author a "just rerun it" variant

This skill runs Monitor → Classify → (Fix | Reproduce → Repair) → loop, every cycle. You may adapt the failure taxonomy, the flake budget, the profile, and the local-reproduction method. You may NOT:

• Declare a flake without the Reproduce state. "The test passed on rerun" is not evidence by itself; reproduce locally first. Blind-rerunning a real, deterministic failure burns CI minutes and never converges.
• Skip Classify and fix everything the same way. Pushing a code change to "fix" a broken runner or a registry outage is noise; infra failures get rerun or reported, not patched.
• Make the loop unbounded. Every path leads to green, a bail with a reason, or the max-iters cap. A babysitter that never reports back is worse than none.

Phase 0: Scope, push, and brief (always done by the main loop)

Do this in the first turn, before launching the workflow.

1. Ensure the branch is pushed and identify the target. The loop watches CI for a commit that exists on the remote, so push first if needed:

   git branch --show-current
   git status -sb            # anything unpushed?
   git push                  # if the branch isn't on the remote / is behind
   gh pr view --json number,headRefName,url 2>/dev/null   # is there a PR?
   gh run list --branch "$(git branch --show-current)" --limit 3 \
     --json databaseId,headSha,status,conclusion,workflowName
   

   Record the PR number (if any) and the branch — the loop watches the most recent run for the head commit.

2. Confirm the push target. This loop pushes fixup commits on its own to trigger fresh CI runs. By default it pushes only to the feature branch and refuses to push to main/master. If HEAD is on a default branch, stop and confirm with the user before running (or pass --allow-push-to-default only when they explicitly want that).

3. Write a short brief to .ci-loop/brief.md: what the change does, any context the fixers can't infer from the diff (env quirks, why a test exists, known-flaky suites, accepted tradeoffs). This is what keeps a fixer from "fixing" intended behavior. The brief is re-Read from disk each phase, so a mid-run edit is honored on the next cycle.

4. mkdir -p .ci-loop and track the run with TodoWrite.

Preferred path: dynamic workflow

When the Workflow tool is available and --inline was not passed, run the loop as a deterministic harness. The bundled script workflow/ci-loop.js is a template — adapt the parameters to the run (the PR/branch, base, profile, flake budget), preferably by passing args rather than rewriting the script.

Template pitfall (read before editing the script): meta must be a pure literal. No string concatenation, no template interpolation, no variables in any field. The Workflow tool rejects anything else with meta must be a pure literal, which breaks every run.

Invoke it via the Workflow tool, passing the Phase 0 artifacts as args:

Workflow({
  scriptPath: "<this skill dir>/workflow/ci-loop.js",
  args: {
    pr:           123,              // PR number, or omit and use branch
    branch:       "<feature branch>",
    base:         "<base branch>",  // for fixup targeting; default main
    brief:        "<contents of .ci-loop/brief.md>",
    briefPath:    ".ci-loop/brief.md",
    profile:      "standard",       // lite | standard | thorough
    flakeRetries: 2,                // per-job rerun budget before escalating
    infraRetries: 2,                // per-run rerun budget for infra failures
    maxIters:     10,               // optional; overrides the profile cap
    allowPushToDefault: false,      // never push to main unless true
  },
})

Profiles are the patience dial (--profile, default standard):

• lite — up to 5 monitor cycles, 3 local reproduction runs per test. A quick pass for a small change you expect to go green fast.
• standard — up to 10 cycles, 5 reproduction runs.
• thorough — up to 20 cycles, 10 reproduction runs. For a long, integration- heavy suite where flakes need more runs to rule out and you want the loop to keep babysitting across many CI cycles.

Model tiering. The bounded/mechanical states run on a cheaper tier: the monitor (watch + report), the classifier (read logs, bucket), the reproduce orchestration (run a test, tally), and reruns all run on Sonnet — that is the floor. The two quality-critical states — the trivial fixer and the test fixer — inherit the strong main-loop model, because a wrong code fix pushed to CI is the expensive mistake. Reproduce is told to bias toward "reproduced" when unsure, so the cheaper judge never silently dismisses a real bug as a flake.

The state machine the workflow runs

Each cycle is one CI observation plus one remediation step; after any push it re-monitors the fresh run (a push re-evaluates everything, so the loop handles one failure class per cycle and lets the next run sort out the rest):

            ┌────────────► Monitor (watch latest run to completion)
            │                  │
            │          green ──┴── failed
            │            │          │
            │          DONE      Classify (lint/build · test · infra)
            │                       │
            │      ┌────────────────┼──────────────────────┐
            │   trivial/build      test                   infra
            │      │                 │                       │
            │    Fix              Reproduce (run locally)   rerun?
            │   (fixup+push)        │                       ├─ budget ► rerun ─┐
            └──── push ◄──┐     ┌───┴────┐                  └─ exhausted ► BAIL │
                         │   flake     reproduced /              (infra)        │
                  ┌──────┘     │       cannot-run                               │
              cannot-fix    rerun?      │                                       │
                 BAIL       ├ budget►rerun ─► (re-monitor) ◄────────────────────┘
                            └ exhausted ► escalate as real
                                            │
                                          Repair (fixer: fix + verify locally + fixup + push)
                                            ├─ fixed ► push ► (re-monitor)
                                            └─ cannot-fix ► BAIL (report to user)

Terminal states the workflow returns in finalState:

• green — CI passed. Done.
• bailed-cannot-fix — the trivial or test fixer could not produce a verified fix; bail.reason carries the user-facing explanation.
• bailed-infra — a non-actionable infra failure persisted past infraRetries.
• stuck — the run is red but nothing actionable could be classified, the reproduce step returned no verdict, or a rerun couldn't be triggered.
• no-ci — no CI run was found for the head commit after the monitor retried (e.g. the push triggered no workflow). Check that CI is wired up for the branch.
• monitor-error — the monitor agent failed to return a result at all.
• maxIters / budget — the safety caps tripped before converging.

It returns a structured summary (finalState, green, profile, iterations, fixesApplied, flakesRerun, bail, history, tokensSpent). The ASCII diagram above shows the happy and bail paths; the safety-cap exits (maxIters, budget, stuck, no-ci, monitor-error) are omitted there for clarity but are all reachable. When it returns, the main loop does Phase 6 (finalize) — autosquash and the final report — because those steps are interactive.

Two behaviors worth knowing when you read the result:

• Flake escalation. A job the reproduce agent calls a "flake" is rerun, but only flakeRetries times. Past that budget the loop stops trusting the flake verdict and escalates the job to the fixer as a real failure — a "flake" that never stops flaking is treated as a bug, not ignored forever.
• Reproduce is conservative by design. "reproduced" and "cannot-run" both go to the fixer (cannot-run because we can't prove it's a flake). Only a clean local result with no diff-side cause earns a rerun-and-move-on.

Report finalState and bail.reason prominently. A bail is a real result to hand back to the user, not a failure of the loop — surface it and ask how to proceed rather than burning more cycles.

Fallback path: in-instance Task dispatch (--inline or no Workflow tool)

Run the same state machine with the Task tool. Track the cycle with TodoWrite.

Monitor

Find the latest run for the head commit (gh run list --branch <b> --json databaseId,headSha,status,conclusion), then watch it (gh run watch <id> --interval 30 --exit-status, or short polling if your shell caps command time). Green → done. Failed → collect failing jobs (gh run view <id> --json conclusion,jobs).

Classify

Spawn one general-purpose agent over gh run view <id> --log-failed. Bucket each failed job: lint (format/static/generated), build (compile), test (assertion — list failing test ids), infra (runner/network/dep outage), other. Be precise about test-assertion vs environment.

Fix (lint/build/other)

One fixer: reproduce the check locally, apply the minimal fix, confirm the local check passes, git commit --fixup=<sha>, and push to the feature branch only (never main/master unless --allow-push-to-default). Re-monitor the new run.

Reproduce (test failures)

One agent runs each failing test locally in isolation N times (go test -run '^T$' -count=N -race ./pkg/...). Verdict per test: reproduced (failed locally — real), flake (passed every local run and no diff-side cause), cannot-run (CI-only env). When unsure, return reproduced, never flake.

Repair (real failures) / rerun (flakes)

• Reproduced / cannot-run → spawn a fixer: root-cause it (do NOT weaken or skip the test), fix, verify locally until green, git commit --fixup=<sha>, push. Re-monitor. If it can't produce a verified fix → bail with a reason.
• Pure flakes within budget → gh run rerun <id> --failed, re-monitor. Past the flake budget → escalate to the fixer as real.
• Infra → gh run rerun <id> --failed within infraRetries, else bail (non-actionable).

Stop at --max-iters and report what remains.

Phase 6: Finalize (always done by the main loop)

1. On green — offer to autosquash the fixups into their originals:

   hunk rebase autosquash --onto <base> --dry-run
   

   Show the plan; on approval run it and force-with-lease push the cleaned history. Declined → leave the fixups as-is.
2. On a bail — report finalState and bail.reason plainly, with what the fixer tried, and ask the user how to proceed. Do not dress a bail up as a pass.
3. Summary (concise, to chat): cycles run, fixes applied (with commits), flakes rerun, and the final CI state with a link to the run.

Notes

• It pushes — that's the point. This loop pushes fixups to your feature branch autonomously to trigger fresh CI runs. It refuses to push to a default branch unless --allow-push-to-default. If you don't want autonomous pushes, use /review-loop (which fixes locally and never pushes) instead.
• GitHub Actions via gh. The template drives gh run / gh pr checks. For another CI provider, adapt the monitor/classify/rerun commands in the agents; the state machine is provider-agnostic.
• Never dismiss a failure as a flake without local evidence. This is the one judgment the loop is built to get right. The reproduce-before-flake rule is load-bearing; do not let an --inline run shortcut it.
• A bail is a clean handoff, not a stop hook to satisfy. When the fixer can't fix it, the most useful thing is a precise report of the failure and what was tried — not another speculative commit.
• Complements /review-loop. Review-loop hardens the diff before you push (adversarial review → fix locally); ci-loop babysits it after (watch CI → fix → push). Run review-loop first, then ci-loop on the pushed branch.