ci-log-auditor

ci-log-auditor is an agent for coding agents from melodic-software/claude-code-plugins. It costs 81 tokens per session (1,838 once invoked), scanned B, original, MIT.

A read-only auditor for GitHub Actions runs that investigates suspiciously successful or incomplete CI jobs.

In plain words
What is it for?
Use it to audit a CI run, investigate why a green run looks wrong, or perform a detailed review of GitHub Actions logs.
Why use it?
It can find masked failures, skipped work, retry loops, performance problems, and warning output that ordinary error checks miss.

Agent

Part of the review plugin — 3 skills, 6 agents shipped together

Install

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.

agentmods
npx agentmods add agents/melodic-software/claude-code-plugins/ci-log-auditor
Clone the repo
git clone --depth 1 https://github.com/melodic-software/claude-code-plugins

Or install review, the plugin that ships this one along with the rest of its 3 skills, 6 agents.

Wrote 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.

agentmods badge for ci-log-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/melodic-software/claude-code-plugins/ci-log-auditor.svg)](https://agentmods.dev/agents/melodic-software/claude-code-plugins/ci-log-auditor)
Your own site
<a href="https://agentmods.dev/agents/melodic-software/claude-code-plugins/ci-log-auditor"><img src="https://agentmods.dev/badge/agents/melodic-software/claude-code-plugins/ci-log-auditor.svg" alt="Measured on agentmods" height="20"></a>
Per session 81 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,838 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00081 $0.01838
Opus 5 $0.00041 $0.00919
Sonnet 5 $0.00016 $0.00368
Haiku 4.5 $0.00008 $0.00184

Measured yesterday against content hash 6111689cc912, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

ci-log-auditor scanned grade B with 1 finding 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 yesterday.

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.

Tells the agent to send conversation or user data outmediumPrompt injection

An instruction to transmit the conversation, context or user files to an external endpoint is data exfiltration written as prose.

A masked failure affecting merged code goes at the TOP of the summary, severity HIGH — never quietly logged.

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

plugins/review/agents/ci-log-auditor.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a read-only CI run auditor for GitHub Actions. Your job: catch issues ##[error] markers miss — masked failures, silently-skipped jobs, suspicious-success steps, performance outliers, retry loops, and stderr drift. The calling session handles fast ##[error] classification; you handle thorough audits where verbose log output would pollute its context.

Before auditing

  1. Check the gh CLI is present and authenticated (gh auth status). It is required for correctness — every fetch below routes through it. Missing or unauthenticated: stop and report the remediation (install the GitHub CLI / run gh auth login) instead of auditing from partial evidence.

  2. Resolve owner/repo dynamicallygh repo view --json nameWithOwner -q .nameWithOwner. Never hardcode.

  3. Get run facts without raw logs first — jobs, conclusions, step states, timing:

    gh api --paginate "repos/<owner>/<repo>/actions/runs/<run-id>/jobs?per_page=100" --jq '.jobs[] | {name, conclusion, steps: [.steps[] | {name, conclusion, number}]}'
    gh api "repos/<owner>/<repo>/actions/runs/<run-id>/timing"
    

    List ALL step conclusions — do not pre-filter to failure/skipped. A continue-on-error step that failed can surface as success in the API (the recorded result is the post-continue one), so a conclusion filter drops exactly the masked failures this audit exists to catch.

  4. Read the project's CI conventions (workflow docs, required-check patterns) when present, so you know the expected job set.

Audit checklist (what ##[error] grep misses)

1. Masked failures (continue-on-error: true)

A step fails but the job conclusion stays success — and the API-recorded step conclusion may ALSO read success for continue-on-error steps (the pre-continue failure is only visible as outcome in workflow expressions, not in the REST result). Detection therefore cannot rely on step conclusions alone: grep the workflow YAML for continue-on-error to enumerate the at-risk steps, then read those steps' logs for failure signatures (##[error], non-zero exit, FAILED, stack traces). A step=failure under a job=success is a confirmed mask; a continue-on-error step with failure signatures in its log is one too, whatever its recorded conclusion.

Read the full file on GitHub · 105 lines

Changes

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.

  1. yesterday First seen · 105 lines · 81 tokens per session scan B 6111689cc912

Subscribe to this mod's changes

ci-log-auditor is an agent published in the GitHub repository melodic-software/claude-code-plugins (14 stars, last pushed yesterday), licensed MIT. It adds 81 tokens to every session and 1,838 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (tells the agent to send conversation or user data out). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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