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/rstackjs/agent-skills/pr-creatornpx skills add rstackjs/agent-skills --skill pr-creatorgit clone --depth 1 https://github.com/rstackjs/agent-skillsWhat 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 | $0.00041 | $0.00724 |
| Opus 5 | $0.00020 | $0.00362 |
| Sonnet 5 | $0.00008 | $0.00145 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
pr-creator 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.
This is a copy
100% identical to pr-creator — 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.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pull Request Creator
Steps
-
Confirm the current branch with
git branch --show-current. If it is the default branch, create and switch to a new branch before doing anything else. Use a descriptive branch name, preferablyfeat-<topic>orfix-<topic>. -
Review local changes with
git status --short. Do not revert unrelated user changes. Before creating the PR, ensure the intended changes are committed and never commit directly on the default branch. -
If
.github/PULL_REQUEST_TEMPLATE.mdexists, read it and follow its structure. -
Draft the PR title in the repository's standard format. If the repository uses Conventional Commits, common patterns include:
feat(core): add ...fix(types): ...docs: ...refactor(types): ...chore(ci): ...for CI workflow, check, or release automation changeschore(deps): ...release: v1.2.0
-
Write the PR body in concise, clear English.
- In
Summary, explain the change context first: the user-facing problem, maintenance goal, or compatibility constraint that makes the change necessary. - Prioritize high-signal information: public API changes, behavior changes, breaking changes, migration notes, and important compatibility implications.
- Then describe the main implementation change only as much as needed to understand the review.
- Keep the PR body concise and review-oriented: use 1-4 short standalone sentences for typical changes, covering why it matters, what changed, and any reviewer-important impact.
- Omit incidental updates to tests, documentation, and supporting artifacts from the PR description; mention them only when they are the PR's primary purpose or carry reviewer-relevant risk.
- Avoid low-signal sections such as
Test planorValidation, routine verification commands, generated file lists, or obvious implementation details unless the repository template explicitly requires them or the change has unusual validation risk. - Good background examples:
This PR adds support for custom logger injection so CLI output can be isolated per instance.This PR fixes incorrect padding in URL labels to keep terminal output aligned across different label lengths.This PR updates the English docs to clarify how the extraction option works and when to enable it.
- In
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 · 57 lines · 41 tokens per session scan A fdb78d1ef2dd
pr-creator is a skill published in the GitHub repository rstackjs/agent-skills (90 stars, last pushed 6d ago), licensed MIT. It adds 41 tokens to every session and 724 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pr-creator, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…