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.
git clone --depth 1 https://github.com/andr-ca/agentharnessWrote 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/rules/andr-ca/agentharness/github-issue-triage)<a href="https://agentmods.dev/rules/andr-ca/agentharness/github-issue-triage"><img src="https://agentmods.dev/badge/rules/andr-ca/agentharness/github-issue-triage/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/andr-ca/agentharness/github-issue-triage"><img src="https://agentmods.dev/badge/rules/andr-ca/agentharness/github-issue-triage.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00040 | $0.01638 |
| Opus 5.5 | $0.00016 | $0.00655 |
| Sonnet 5.5 | $0.00008 | $0.00328 |
| Haiku 4.5 | $0.00004 | $0.00164 |
Grade A, and why
github-issue-triage 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 1mo 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Issue Triage
Assess a GitHub issue by verifying its claims against actual code, checking fit against product vision, and leaving a structured comment with findings, corrections, and a test plan. This skill assesses and comments — it does not implement fixes. Fixes follow a separate deliberate step per this repo's Recommendation Assessment mandate in CLAUDE.md.
The Prompt (canonical form)
Triage issue #N. Start by fetching the full issue details (title, body, comments, labels, linked PRs). Then verify every factual claim in the issue against the actual running code — grep the relevant source, read the actual files/lines, and where feasible run the relevant code path (in a scratch/sandboxed way) to confirm it's real, not stale, not a misunderstanding. Check the ask against roadmap/vision docs (ROADMAP.md, ARCHITECTURE.md, DECISIONS.md, MANIFEST.md) and note whether it's a scoped fix vs. a bigger direction-setting ask needing human scoping. Draft and post a
gh issue commentwith: confirmed findings with evidence, corrections to stale/wrong claims, a recommendation per CLAUDE.md's Recommendation Assessment mandate, and concrete test/verification steps for the fix. Report what you found and what you posted.
Procedure
1. Fetch the issue
Run gh issue view <n> --json title,body,comments,labels,linkedPullRequests.
Extract:
- Title and body (claims to verify)
- All comments (context, earlier findings, clarifications)
- Labels (priority, type, status signals)
- Linked PRs (related work, partial fixes, predecessor context)
2. Verify every factual claim against running code
This is the hardest step and the highest leverage. Do not trust the issue's prose — verify against the source.
For each claim:
- File changes: Does the file exist?
test -e <path>. Read it and check the actual line/section. - Behavior claims: Grep for the relevant code path. If feasible, run it in a scratch/sandboxed context (e.g., a test, a manual script in a temp directory, a clone of this repo or the repo's dependency) to observe actual behavior.
- "Already fixed" archaeology: Run
git log --all -p --grep=<keyword>orgit log --all -S<string>to check whether a claimed-broken thing was already fixed by a later commit on a different branch or after the issue was filed. - Misunderstandings: If the claim rests on a false premise (wrong file path, misread config, older API surface), note that explicitly.
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.
- 1mo ago First seen · 119 lines · 40 tokens per session scan A faf156f548aa
github-issue-triage is a cursor rule published in the GitHub repository andr-ca/agentharness (1 stars, last pushed 5d ago), licensed MIT. It adds 40 tokens to every session and 1,638 once invoked, about $0.0002 per session on Opus 5.5. 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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