Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/oolab-labs/patchwork-os/fix-cigit clone --depth 1 https://github.com/Oolab-labs/patchwork-osWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00010 | $0.00506 |
| Opus 5 | $0.00005 | $0.00253 |
| Sonnet 5 | $0.00002 | $0.00101 |
| Haiku 4.5 | $0.00001 | $0.00051 |
Grade A, and why
fix-ci scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Fix Failing CI
Diagnose the failing CI run $1 (a workflow run id, or a PR number whose checks are red — if omitted, use the most recent failing run on the current branch).
Step 1: Locate the Failing Run
If $1 is a PR number, call githubViewPR to find its check runs. Otherwise
call githubListRuns and pick the most recent failure on the current branch.
Report the run id and which job(s) failed.
Step 2: Pull the Logs
Call githubGetRunLogs for the failing run. Identify the failing step and the
first real error — not downstream noise. Common failure shapes in this repo:
- typecheck —
tsc -p tsconfig.tests.core.jsonis stricter than vitest (noUnusedLocals); import-path errors slip past local vitest runs. - biome — run
getDiagnosticsto reproduce; nevernpx biomeblindly. - vitest — coverage gates are 75% lines / 70% branches / 75% functions.
- property tests — may pass locally and fail in CI on a different seed; pin the failing seed from the CI output.
- Windows CI —
stat.modeasserts fail on NTFS; platform-guard them.
Step 3: Reproduce Locally
Reproduce the failure with the equivalent bridge tool — runTests,
getDiagnostics (replaces tsc/eslint/biome) — NOT raw shell. Confirm you see
the same error before proposing anything.
Step 4: Propose the Fix
If the failure is a genuine bug, follow the Bug Fix Protocol: write a failing test first, then fix. If it is a flake (seed-dependent property test, etc.), pin the seed or tighten the generator. Present the diff to the user for approval before committing.
Step 5: Report to User
Show: the failing job, the root-cause error, whether it reproduced locally, and the proposed fix (or the failing test, if a fix needs approval first).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 49 lines · 10 tokens per session scan A 9d1e80ba6e98
fix-ci is a command published in the GitHub repository Oolab-labs/patchwork-os (30 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 506 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.