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/sandeep-alluru/groundcrew/pr-prepgit clone --depth 1 https://github.com/sandeep-alluru/groundcrewWrote 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/sandeep-alluru/groundcrew/pr-prep)<a href="https://agentmods.dev/commands/sandeep-alluru/groundcrew/pr-prep"><img src="https://agentmods.dev/badge/commands/sandeep-alluru/groundcrew/pr-prep.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 | $0.00000 | $0.00184 |
| Opus 5 | $0.00000 | $0.00092 |
| Sonnet 5 | $0.00000 | $0.00037 |
| Haiku 4.5 | $0.00000 | $0.00018 |
Grade A, and why
pr-prep 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 3d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
- pr-prep — 100% identical, 0 lines differ
What it actually says
Run the full pre-PR checklist and report what's ready and what needs fixing.
Steps:
- Run lint:
make lint(ruff check + ruff format --check) - Run type check:
make typecheck(mypy) - Run tests:
make test(pytest with coverage) - Check CHANGELOG.md has an entry under [Unreleased] for this change
- Check that no debug print() statements or TODO comments were left in modified files
Report in this format: ✅ Lint — clean ✅ Types — clean ✅ Tests — 43 passed, 87% coverage ⚠️ CHANGELOG — no [Unreleased] entry found ✅ No debug artifacts
If anything fails, show the exact error and the file:line to fix. Do not mark the PR ready until all 5 checks pass.
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.
- 3d ago First seen · 19 lines · 0 tokens per session scan A bdaef57ccde0
pr-prep is a command published in the GitHub repository sandeep-alluru/groundcrew (0 stars, last pushed 16d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 184 tokens. 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
fix
Act on the findings a review left on a PR — takes or declines each by severity, edits code at pwd to match the project, 1 commit, replies once pushed.
/commit-push
Commit and push all changes from this chat session using Conventional Commits.
pr
Commit all changes, push to remote, and create a pull request.
commit
Create a git commit with proper formatting and AI-Used trailer.
clean
Tidy and sync — commit changed notes, clear processed Inbox (with approval), and push.
ci_commit
Create git commits for session changes with clear, atomic messages.