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 commands/jayminwest/canopy/issue-reviewsgit clone --depth 1 https://github.com/jayminwest/canopyWrote 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/commands/jayminwest/canopy/issue-reviews)<a href="https://agentmods.dev/commands/jayminwest/canopy/issue-reviews"><img src="https://agentmods.dev/badge/commands/jayminwest/canopy/issue-reviews.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 | $0.00003 | $0.00774 |
| Opus 5 | $0.00002 | $0.00387 |
| Sonnet 5 | $0.00001 | $0.00155 |
| Haiku 4.5 | $0.00000 | $0.00077 |
Grade A, and why
issue-reviews 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 4d 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.
This is a copy
91% identical to issue-reviews — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
intro
Review open GitHub issues for priority, feasibility, project alignment, and risks.
Argument: $ARGUMENTS — optional issue number(s) to review (e.g., 5 or 5 8 12). If empty, review all open issues.
Steps
1. Discover issues to review
- If
$ARGUMENTScontains issue number(s), use those - Otherwise, run
gh issue list --state open --json number,title,author,labels,createdAt,updatedAt,commentsto get all open issues - If there are no open issues, say so and stop
2. Spawn a review team
Use the Task tool to spawn parallel agents (one per issue, or batch small sets if there are many). Each agent should:
a. Gather context
gh issue view <number> --json title,body,author,labels,comments,createdAt,updatedAt- Read any files referenced in the issue body or comments
- Search the codebase for related code (
Grep/Globfor keywords, function names, file paths mentioned) - Check if there are related open PRs:
gh pr list --state open --search "<issue-title-keywords>"
b. Feasibility assessment
- Is the issue well-defined enough to act on?
- What files/subsystems would need to change?
- Estimate scope: small (1-2 files), medium (3-5 files), large (6+ files / architectural)
- Are there prerequisite changes or dependencies on other issues?
- Are there technical blockers or unknowns?
c. Project alignment review
- Does this issue align with canopy's goals (prompt management & composition, minimal dependencies, Bun-native)?
- Does it conflict with existing architecture decisions?
- Is it a feature request, bug fix, improvement, or maintenance task?
- Would addressing it create technical debt or reduce it?
d. Risk assessment
- What could go wrong if this is implemented naively?
- Are there breaking changes or migration concerns?
- Does it touch critical infrastructure (config, prompt store, schemas, emit pipeline)?
- Could it introduce performance regressions?
- Are there security implications?
e. Priority recommendation
- Critical — Blocks users or breaks core functionality
- High — Significant improvement, clear path to implement
- Medium — Useful but not urgent, well-scoped
- Low — Nice-to-have, unclear scope, or minimal impact
- Wontfix — Doesn't align with project direction, or cost outweighs benefit
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.
- 4d ago First seen · 76 lines · 3 tokens per session scan A 4b49a59fcce3
issue-reviews is a command published in the GitHub repository jayminwest/canopy (40 stars, last pushed 1mo ago), licensed MIT. It adds 3 tokens to every session and 774 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to issue-reviews, differing in 6 lines, and is treated as a copy.
Other commands, from other repositories
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快速创建和管理AI团队会议.
workspace
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standup
Show a daily standup summary with completed, in-progress, and blocked tasks across all active epics.
m-task-planner
Target: $ARGUMENTS (Default: requirement document(s) discovered in the project).
triage
Triage ServiceNow incidents — list open incidents, assess priority, investigate a specific INC, or analyze trends.