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-loop-lifecyclenpx skills add jl-cmd/claude-dev-env --skill pr-loop-lifecyclegit clone --depth 1 https://github.com/jl-cmd/claude-dev-envWhat 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 | $0.00080 | $0.01204 |
| Opus 5 | $0.00040 | $0.00602 |
| Sonnet 5 | $0.00016 | $0.00241 |
| Haiku 4.5 | $0.00008 | $0.00120 |
Grade B, and why
pr-loop-lifecycle scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
The script writes idempotent allow-rules and `additionalDirectories` entries into `~/.claude/settings.json` so subagents can edit the project's `.claude/` tree without prompting. How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Loop Lifecycle
Core principle: a PR-loop run opens with an explicit, revocable permission grant and closes the same way every time — teardown, description rewrite, revoke, report — no matter how the run ended.
How callers invoke this
- Skill-capable contexts (a lead session with the
Skilltool):Skill({skill: "pr-loop-lifecycle", args: "--skill <caller> <open|close> [parameters]"}). - Fallback (a subagent or teammate without the
Skilltool): the caller's spawn prompt says "Read~/.claude/skills/pr-loop-lifecycle/SKILL.mdand apply the<open|close>section with the parameters below."
The caller passes its identity (fills the final-report header and scratch-file prefix), whether it runs an agent team (gates the TeamDelete step), and at close time the run's exit reason, loop count, and SHAs.
Open
-
Grant project permissions:
python "$HOME/.claude/_shared/pr-loop/scripts/grant_project_claude_permissions.py"The script writes idempotent allow-rules andadditionalDirectoriesentries into~/.claude/settings.jsonso subagents can edit the project's.claude/tree without prompting.Auto-mode escalation: in an unattended run the permission classifier can block this grant as an unrequested allowlist change. Keep the run alive — surface the exact command to the user through
AskUserQuestionand ask them to approve it or run it themselves with the!prefix. Continue once the grant lands. A user who wants future runs to skip the prompt can add a standing Bash allow-rule for the script in their settings. -
Worktree preflight: confirm the session is isolated (the working directory path includes
.claude/worktrees/) before the first tick or round. Classify the working tree against the PR's repo withpython "$HOME/.claude/skills/_shared/pr-loop/scripts/preflight_worktree.py" --owner <O> --repo <R> --mode <classify|strict>and route per the caller's cwd-routing reference (pr-converge Step 1.5 for the classify route; autoconverge pre-flight for the strict route). Capture the session worktree path before routing away — close-time steps target the session repo.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 70 lines · 80 tokens per session scan B 59733f8e6b40
pr-loop-lifecycle is a skill published in the GitHub repository jl-cmd/claude-dev-env (6 stars, last pushed 2d ago), licensed MIT. It adds 80 tokens to every session and 1,204 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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.
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…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
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.