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 skills/jl-cmd/claude-dev-env/pr-small-clnpx skills add jl-cmd/claude-dev-env --skill pr-small-clgit clone --depth 1 https://github.com/jl-cmd/claude-dev-envWrote 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/skills/jl-cmd/claude-dev-env/pr-small-cl)<a href="https://agentmods.dev/skills/jl-cmd/claude-dev-env/pr-small-cl"><img src="https://agentmods.dev/badge/skills/jl-cmd/claude-dev-env/pr-small-cl.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 | $0.00040 | $0.00414 |
| Opus 5 | $0.00020 | $0.00207 |
| Sonnet 5 | $0.00008 | $0.00083 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
pr-small-cl 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 5d 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.
What it actually says
Focused Pull Request Guide
When to Use This Guide
Use this guide to plan, assess, or split a pull request into a reviewable unit. The pull request boundary is conceptual: one coherent outcome that a reviewer can understand with its context and verification.
What a Focused Pull Request Contains
A focused pull request contains the implementation, related tests, documentation, and configuration needed for one outcome. It leaves the system in a usable state and gives the reviewer the information needed to assess the change.
Use the description guide to record the scope, verification, risks, and follow-up work.
Splitting a Change
Choose a split that gives each increment a coherent purpose and a clear test boundary. Useful seams include:
- Preparation refactors followed by behavior changes.
- Independent vertical features that each deliver a user-visible capability.
- Layer-specific work when each layer remains independently understandable.
- Stacked changes when each earlier change supplies the next change's stable foundation.
State dependencies between related pull requests and keep each increment safe to merge or revert on its own.
Reviewable Scope
Ask to split a change when its breadth prevents a reliable assessment of design, behavior, or verification. Identify the first coherent increment and the remaining increments so the author has an actionable path forward.
Use reviews to evaluate the resulting scope and emergencies when an active incident sets the immediate boundary.
Responding to Review
Use the comment guide to respond to feedback and resolve pushback.
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.
- 5d ago First seen · 53 lines · 40 tokens per session scan A dd00d0fc4aee
pr-small-cl is a skill published in the GitHub repository jl-cmd/claude-dev-env (5 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 414 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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