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 skills add stark-ai-de/agent-skills --skill ci-debuggergit clone --depth 1 https://github.com/stark-ai-de/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/stark-ai-de/agent-skills/ci-debugger)<a href="https://agentmods.dev/skills/stark-ai-de/agent-skills/ci-debugger"><img src="https://agentmods.dev/badge/skills/stark-ai-de/agent-skills/ci-debugger.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00056 | $0.00655 |
| Opus 5 | $0.00028 | $0.00328 |
| Sonnet 5 | $0.00011 | $0.00131 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
ci-debugger 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI Debugger
Goal
Find the first meaningful CI failure, explain the root cause with evidence, propose the smallest fix, and recommend the validation command that should prevent recurrence.
When to use
- A CI, build, deploy, or package-manager job failed.
- The user provides logs, a run URL, or asks to inspect CI live.
- Long logs need targeted extraction instead of full dumping.
When not to use
- The user asks for broad repo health rather than one failed pipeline.
- The failure requires production incident response beyond CI diagnosis.
- The user wants dependency risk review without a failing job; use
dependency-update-review.
Inputs
- CI provider, workflow/job name, run URL, failed step, and logs.
- Package manager output, build artifacts, test reports, and recent diffs.
- Repo scripts, workflow YAML, and environment requirements.
Inputs to inspect
- Inspect the failed step, first meaningful error, relevant workflow config, package scripts, and changed files.
- Use targeted log excerpts instead of dumping full logs.
Process
- Identify the failed job and failed step.
- Extract the first meaningful error, not the last cascade.
- Search logs with targeted patterns and inspect nearby context.
- Map the failure to code, config, dependency, environment, or infra.
- Propose a minimal fix and a regression validation command.
- Avoid broad rewrites unless the failure proves a systemic issue.
Workflow
Follow the process above and verify the minimal fix locally when possible. Report skipped live CI checks explicitly.
Decision points
- If logs are incomplete, ask for the failed step or run URL.
- If credentials or external services are required, separate local validation from live validation.
- If multiple jobs fail, group by shared root cause before fixing each.
Safety rules
- Do not paste full secrets from logs.
- Do not rerun expensive or write-capable workflows without approval.
- Do not assume downstream failures are separate bugs until the first failure is resolved.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 96 lines · 56 tokens per session scan A eacb4978834a
ci-debugger is a skill published in the GitHub repository stark-ai-de/agent-skills (5 stars, last pushed 4d ago), licensed Apache-2.0. It adds 56 tokens to every session and 655 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
openlore-debug
Debug with OpenLore structural context, an explicit root-cause hypothesis, and RED/GREEN verification. Use when a bug, failure, or regression needs diagnosis and repair.
openlore-analyze-codebase
Run a full static OpenLore analysis and summarize architecture, call graph, refactoring issues, and duplicate code. Use when asked to analyze, map, or assess a codebase without LLM inference.
actions-debugging
Use when a GitHub Actions workflow fails — diagnose the run log, identify the root cause, and apply a targeted fix.
gh-fix-ci
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use gh to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
diagnose-ci-failures
Diagnose failing CI, lint, typecheck, build, or test logs and propose or implement the smallest verified fix.
sling
Diagnoses GitHub Actions failures and attributes CI time and cost using StarSling's sling CLI. Invoke this BEFORE using gh or fetching any logs whenever the user asks why a job or run failed, what made a run slow, about runner minutes or CI cost, asks to re-run or cancel a run, or pastes a GitHub Actions URL — sling…