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-shared-extractionnpx skills add jl-cmd/claude-dev-env --skill pr-shared-extractiongit 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-shared-extraction)<a href="https://agentmods.dev/skills/jl-cmd/claude-dev-env/pr-shared-extraction"><img src="https://agentmods.dev/badge/skills/jl-cmd/claude-dev-env/pr-shared-extraction.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 | $0.00091 | $0.01971 |
| Opus 5 | $0.00046 | $0.00986 |
| Sonnet 5 | $0.00018 | $0.00394 |
| Haiku 4.5 | $0.00009 | $0.00197 |
Grade A, and why
pr-shared-extraction 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.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shared Extraction Audit
Audit PRs and packages for reusable behavior placed in workflow code. Keep orchestration packages thin and shared_utils canonical.
When to use
- User points at a PR (e.g.
#1954,#1965) and asks for the same review loop - A package grew
fix_one,_default_*, backup upload, rembg session, or residual gates alongside orchestration - Before merge: confirm consumers are adapters, not second implementations
Mode routing
Resolve the first matching mode before the audit steps:
preflight-proposalrunspr-shared-extraction preflight-proposal <pr_number> --base-sha <base_sha> --head-sha <head_sha> --worktree <isolated_worktree>under the shared preflight proposal contract. Record each finding with priority and target.audit-onlyis report-only and ends after the findings report.- Normal mode follows the existing audit workflow and applies the prioritized fix band by default.
Target architecture
| Layer | Holds | Examples |
|---|---|---|
| shared_utils | Reusable actions, I/O, DB flips, inference, constants used by 2+ workflows | status_promotion, background_removal, drive_production_backup, stp_filenames |
| Workflow package | Orchestration, CLI, sweep loops, workflow-specific constants only | cert_fix_queue/pipeline/queue_run.py, theme_dialer_pipeline compose runners |
| Skills / scripts | Operator entrypoints that delegate to shared_utils | No parallel rembg/session stacks |
Load-bearing rule: If another package would import it, put it in shared_utils. After the move, every former caller imports the shared symbol and the old module is deleted.
Audit workflow
Register this checklist with update_plan and mark each step complete with evidence:
Shared extraction audit:
- [ ] 1. Scope the PR (base branch, changed packages, stated goal)
- [ ] 2. Map canonical homes already in shared_utils
- [ ] 3. Grep for offense patterns (see reference/offense-taxonomy.md)
- [ ] 4. Write prioritized findings (P0–P3)
- [ ] 5. Apply **Mode routing** after the report
- [ ] 6. Extract in small CLs (~100 lines) + move/adjust tests
- [ ] 7. Run scoped pytest, then follow the selected mode's mutation boundary
- [ ] 8. When the mode is `preflight-proposal`, record proposal evidence from the [shared preflight proposal contract](../_shared/pr-loop/preflight-proposal.md) and require downstream owner selection before reapplication
What ships with it
2 files 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.
- 3d ago First seen · 178 lines · 91 tokens per session scan A 49ca716d1857
pr-shared-extraction is a skill published in the GitHub repository jl-cmd/claude-dev-env (6 stars, last pushed 3d ago), licensed MIT. It adds 91 tokens to every session and 1,971 once invoked, about $0.0005 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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