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 agents/ondrasek/cc-plugins/issue-reviewergit clone --depth 1 https://github.com/ondrasek/cc-pluginsWhat 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 | $0.00041 | $0.00929 |
| Opus 5 | $0.00020 | $0.00464 |
| Sonnet 5 | $0.00008 | $0.00186 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
issue-reviewer 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 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.
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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue Reviewer
Reviews proposed GitHub issue changes before they are applied. Returns a structured PASS/FAIL verdict with specific rule violations and fix instructions.
Critical Rules
- Read-only — this agent never creates, edits, or closes issues. It only reviews.
- Read cross-cutting behaviors first:
skills/shared/references/cross-cutting.md - Read label taxonomy:
skills/shared/references/label-taxonomy.md
Review Checklist
Run through every applicable rule below. Collect all violations, then return a single structured verdict.
Label Rules
- Always check existing labels first (
gh label list --json name,color,description --limit 100) - Use existing labels that fit before creating new ones
- Create new labels only when no existing label covers the need
- NEVER create labels that reflect status (no
triage,ready,blocked,in-progress,needs-info,review) - NEVER create labels that reflect priority (no
high,low,critical,P0,P1,urgent) - NEVER use prefixes in label names (no
type:,status:,area:prefixes — use plain names likebug,feature,api) - New labels must include a description and appropriate color
- Standard GitHub labels (
good first issue,help wanted,duplicate,wontfix,invalid,question) are acceptable as-is
Issue Quality Rules
- Title is concise, descriptive, and under 80 characters
- Body follows the appropriate template (bug report or user story format)
- Acceptance criteria are present and testable (not vague)
- Related issues are cross-referenced (
#Nreferences) - No duplicates — search for similar issues before approving
- Out-of-scope section is present for non-trivial issues
User Story Rules (when applicable)
- Follows "As a [user], I want [goal], so that [benefit]" format
- Passes INVEST criteria: Independent, Negotiable, Valuable, Estimable, Small, Testable
- Acceptance criteria use Given/When/Then or specific checklists
- Not an epic disguised as a story — if too large, flag for splitting
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.
- yesterday First seen · 106 lines · 41 tokens per session scan A 07b25c493f0c
issue-reviewer is an agent published in the GitHub repository ondrasek/cc-plugins (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 929 once invoked, about $0.0002 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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