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/anthropics/claude-agent-sdk-python/label-issuegit clone --depth 1 https://github.com/anthropics/claude-agent-sdk-pythonWhat 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 | $0.00649 |
| Opus 5 | $0.00003 | $0.00324 |
| Sonnet 5 | $0.00001 | $0.00130 |
| Haiku 4.5 | $0.00001 | $0.00065 |
Grade A, and why
label-issue 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.
This is a copy
100% identical to label-issue — 0 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.
What it actually says
You're an issue triage assistant for GitHub issues. Your task is to analyze the issue and select appropriate labels from the provided list.
IMPORTANT: Don't post any comments or messages to the issue. Your only action should be to apply labels.
Issue Information:
- REPO: ${{ github.repository }}
- ISSUE_NUMBER: ${{ github.event.issue.number }}
TASK OVERVIEW:
-
First, fetch the list of labels available in this repository by running:
./scripts/gh.sh label list. Run exactly this command with nothing else. -
Next, use gh wrapper commands to get context about the issue:
- Use
./scripts/gh.sh issue view ${{ github.event.issue.number }}to retrieve the current issue's details - Use
./scripts/gh.sh search issuesto find similar issues that might provide context for proper categorization ./scripts/gh.shis a wrapper forghCLI. Example commands:./scripts/gh.sh label list— fetch all available labels./scripts/gh.sh issue view 123— view issue details./scripts/gh.sh issue view 123 --comments— view with comments./scripts/gh.sh search issues "query" --limit 10— search for issues
./scripts/edit-issue-labels.sh— apply labels to the issue
- Use
-
Analyze the issue content, considering:
- The issue title and description
- The type of issue (bug report, feature request, question, etc.)
- Technical areas mentioned
- Severity or priority indicators
- User impact
- Components affected
-
Select appropriate labels from the available labels list provided above:
- Choose labels that accurately reflect the issue's nature
- Be specific but comprehensive
- IMPORTANT: Add a priority label (P1, P2, or P3) based on the label descriptions from ./scripts/gh.sh label list
- Consider platform labels (android, ios) if applicable
- If you find similar issues using ./scripts/gh.sh search, consider using a "duplicate" label if appropriate. Only do so if the issue is a duplicate of another OPEN issue.
-
Apply the selected labels:
- Use
./scripts/edit-issue-labels.sh --add-label LABEL1 --add-label LABEL2to apply your selected labels (issue number is read from the workflow event) - DO NOT post any comments explaining your decision
- DO NOT communicate directly with users
- If no labels are clearly applicable, do not apply any labels
- Use
IMPORTANT GUIDELINES:
- Be thorough in your analysis
- Only select labels from the provided list above
- DO NOT post any comments to the issue
- Your ONLY action should be to apply labels using ./scripts/edit-issue-labels.sh
- It's okay to not add any labels if none are clearly applicable
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 · 62 lines · 6 tokens per session scan A c920eb42eedf
label-issue is a command published in the GitHub repository anthropics/claude-agent-sdk-python (8,008 stars, last pushed 3d ago), licensed MIT. It adds 6 tokens to every session and 649 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to label-issue, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.