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 skills add chrisallenlane/claude-swe-workflows --skill lead-reviewgit clone --depth 1 https://github.com/chrisallenlane/claude-swe-workflowsWrote 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/chrisallenlane/claude-swe-workflows/lead-review)<a href="https://agentmods.dev/skills/chrisallenlane/claude-swe-workflows/lead-review"><img src="https://agentmods.dev/badge/skills/chrisallenlane/claude-swe-workflows/lead-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chrisallenlane/claude-swe-workflows/lead-review"><img src="https://agentmods.dev/badge/skills/chrisallenlane/claude-swe-workflows/lead-review.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00115 | $0.05122 |
| Opus 5 | $0.00057 | $0.02561 |
| Sonnet 5 | $0.00023 | $0.01024 |
| Haiku 4.5 | $0.00012 | $0.00512 |
Grade A, and why
lead-review 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 12d 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 — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead-Review — Autonomous Comprehensive Review
Drives a codebase through every review dimension — orientation, architecture, security, performance, accessibility, tests, release-readiness — without operator involvement between startup and termination. The operator states scope, whether tickets should be cut, and (if so) the severity floor for ticket creation. The skill then runs each enabled sub-skill in sequence, auto-approving or auto-declining ticket proposals uniformly per the startup choice. Termination is structural — once all enabled sub-skills have run, the consolidated report is produced.
This skill is the successor to /review-deep. The v10 move into the /lead-* namespace makes the autonomy-axis identity explicit; the redesign trades interactive participation for autonomous execution and adds the ticket-creation toggle so the run can serve both "produce a comprehensive backlog" and "produce a comprehensive audit report" use cases.
Philosophy
This skill implements the autonomy discipline documented in references/autonomy.md. The shared discipline governs the five levers (altitude rule, pre-loaded options, pre-rebutted recommendation, commander's intent, risk budgets), the cascade rule, the no-unilateral-breaking-changes guardrail, and the shared handoff template.
Two modes from one workflow
The same pipeline serves two operator intents:
- Backlog generation (tickets ON) — autonomous review-driven ticket creation. The skill runs every enabled review sub-skill, auto-approves each one's ticket proposals at or above the severity floor, and produces a consolidated, batch-tagged backlog the operator can feed to
/implement-projector/lead-refactor. - Audit report (tickets OFF) — autonomous comprehensive audit. The skill runs every enabled review sub-skill, auto-declines all ticket proposals uniformly, and surfaces all findings in the consolidated completion report. No tracker writes.
The operator chooses at startup. There is no mid-run switching.
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.
- 12d ago First seen · 399 lines · 115 tokens per session scan A f0dc9035e56d
lead-review is a skill published in the GitHub repository chrisallenlane/claude-swe-workflows (18 stars, last pushed 3mo ago), licensed MIT. It adds 115 tokens to every session and 5,122 once invoked, about $0.0006 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 2026-08-30.
Other skills, from other repositories
afc:learner
Review and promote learned patterns to project rules.
afc:architect
Architecture analysis and design review.
afc:pr-comment
Post structured review comments to GitHub PR.
afc:resolve
Address LLM bot review comments on PR — fix valid issues, dismiss false positives.
afc:review
Code review — review code, analyze PR diff, evaluate quality and correctness.
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…