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 skills/nanasess/eccube-dev-agents/github-logs-analyzenpx skills add nanasess/eccube-dev-agents --skill github-logs-analyzegit clone --depth 1 https://github.com/nanasess/eccube-dev-agentsWrote 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/nanasess/eccube-dev-agents/github-logs-analyze)<a href="https://agentmods.dev/skills/nanasess/eccube-dev-agents/github-logs-analyze"><img src="https://agentmods.dev/badge/skills/nanasess/eccube-dev-agents/github-logs-analyze.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 | $0.00006 | $0.00815 |
| Opus 5 | $0.00003 | $0.00407 |
| Sonnet 5 | $0.00001 | $0.00163 |
| Haiku 4.5 | $0.00001 | $0.00081 |
Grade A, and why
github-logs-analyze 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 3d 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
GitHub Actions ログ解析
GitHub Actions の失敗ログを解析し、失敗したテストとエラー原因を特定します。
手順
1. 引数解析
$ARGUMENTS から job 情報を抽出:
- URL形式の場合:
https://github.com/{owner}/{repo}/actions/runs/{run_id}/job/{job_id}からowner,repo,job_idを抽出 - 数字のみの場合: job ID として扱う
- owner/repo の特定:
- URLから抽出できる場合はそれを使用
- できない場合は
gh repo view --json nameWithOwner -q .nameWithOwnerでカレントリポジトリから取得
2. ジョブ情報取得
gh api repos/{owner}/{repo}/actions/jobs/{job_id} でジョブ詳細を取得:
- Job名
- 実行時間(started_at, completed_at)
- ステータス(conclusion)
- 各 step の名前とステータス
- 失敗した step を特定
3. ログ取得と解析
gh api repos/{owner}/{repo}/actions/jobs/{job_id}/logs でログを取得し解析:
テストフレームワーク別の失敗パターン検出:
PHPUnit:
FAILURES!/ERRORS!Tests: X, Assertions: Y, Failures: Z1) TestClass::testMethodFailed asserting that ...
Codeception:
FAILURES!Couldn't .../Failed ...
Jest:
FAIL src/...● Test Suite > test nameExpected ... Received ...
pytest:
FAILED tests/...E assert ...
一般的なエラーパターン:
Error:/Exception:fatal:/panic:- タイムアウト:
timeout/exceeded - メモリ不足:
out of memory/Allowed memory size
4. 結果表示
## Job 概要
- Job名: <name>
- 実行時間: <duration>
- 失敗 Step: <step name>
## 失敗テスト一覧
❌ TestClass::testMethod
エラー: <エラーメッセージ>
ファイル: <path>:<line>
❌ TestClass::testMethod2
エラー: <エラーメッセージ>
ファイル: <path>:<line>
## エラー原因の推定
<原因の分析と修正提案>
5. job ID 未指定の場合
gh run list --status=failure --limit=5で最新の失敗 run を表示- ユーザーに調査対象を選択してもらう
- 選択された run の jobs を
gh run view {run_id} --json jobsで取得 - 失敗した job のログを解析
エラーハンドリング
- job ID が見つからない場合: 正しい URL/ID 形式を案内
- ログが空または取得できない場合: run レベルのログ取得を試行
- リポジトリへのアクセス権がない場合:
gh auth loginを案内
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.
- 3d ago First seen · 96 lines · 6 tokens per session scan A 4f0224c5ff9f
github-logs-analyze is a skill published in the GitHub repository nanasess/eccube-dev-agents (2 stars, last pushed 28d ago), licensed MIT. It adds 6 tokens to every session and 815 once invoked, about $0.0000 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.
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