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/notorious-ai/claude-pluginsWrote 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/notorious-ai/claude-plugins/draft-pr)<a href="https://agentmods.dev/commands/notorious-ai/claude-plugins/draft-pr"><img src="https://agentmods.dev/badge/commands/notorious-ai/claude-plugins/draft-pr/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/commands/notorious-ai/claude-plugins/draft-pr"><img src="https://agentmods.dev/badge/commands/notorious-ai/claude-plugins/draft-pr.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 | $0.00008 | $0.00814 |
| Opus 5.5 | $0.00003 | $0.00326 |
| Sonnet 5.5 | $0.00002 | $0.00163 |
| Haiku 4.5 | $0.00001 | $0.00081 |
Grade A, and why
draft-pr 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Draft Pull Request
Gather git context and draft an effective pull request using the writing-pull-requests skill. Focus on surfacing the why - intent, constraints, and rationale - that the diff cannot convey.
Step 1: Gather Git Context
Collect information about the current branch:
Branch and commits:
!git branch --show-current && echo "---" && git log --oneline main..HEAD 2>/dev/null | head -15
Files changed:
!git diff main...HEAD --stat 2>/dev/null | tail -15
Step 2: Search for Related Work
Check for related issues and PRs:
Open issues:
!gh issue list --state open --limit 8 2>/dev/null || echo "Could not fetch issues"
Recent PRs:
!gh pr list --state all --limit 5 2>/dev/null || echo "Could not fetch PRs"
Step 3: Surface the Hidden Context
Use probe questions to uncover what the diff cannot show. The writing-pull-requests skill guides what context to capture - focus on:
- Expected outcome - what the change accomplishes (verifiable against the changeset)
- Constraints that shaped the solution - technical, organizational, or timeline limitations
- Designed exclusions - what this change explicitly does not address and why
- Reevaluation triggers - conditions under which to revisit this decision
Ask clarifying questions:
- "What constraint prevented the simpler solution?"
- "What is explicitly out of scope, and why?"
- "Under what conditions should we revisit this approach?"
Use AskUserQuestion if purpose is unclear:
- question: "What problem does this PR solve or what value does it add?"
- header: "Motivation"
- options:
- Bug fix (Corrects incorrect behavior)
- New feature (Adds new capability)
- Improvement (Enhances existing functionality)
- Refactoring (Restructures without behavior change)
Check for linked issues:
- question: "Is there a related issue to link?"
- header: "Issue link"
- options:
- Yes (I'll provide the issue number)
- No issue exists (The PR description will provide context)
- Search again (Help me find related issues)
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 · 97 lines · 8 tokens per session scan A 134d43817730
draft-pr is a command published in the GitHub repository notorious-ai/claude-plugins (5 stars, last pushed 1mo ago), licensed MIT. It adds 8 tokens to every session and 814 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
speckit.spex.submit
Push and create PR for team review, with optional watch mode for CI monitoring.
git
The pre-finish status: branch, hygiene findings, message checks, workflow lint, template state.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
release-tag
Create and push a version tag after a release PR has been merged.
factory
Linha de montagem multi-agente (Software Factory) — spec-writer → builder em worktree isolado → 4 revisores paralelos (Security, Code, UI, UX) → approver com gate de risco e dashboard visual.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.