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-projectgit 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-project)<a href="https://agentmods.dev/skills/chrisallenlane/claude-swe-workflows/lead-project"><img src="https://agentmods.dev/badge/skills/chrisallenlane/claude-swe-workflows/lead-project/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-project"><img src="https://agentmods.dev/badge/skills/chrisallenlane/claude-swe-workflows/lead-project.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 | $0.00082 | $0.07079 |
| Opus 5 | $0.00041 | $0.03540 |
| Sonnet 5 | $0.00016 | $0.01416 |
| Haiku 4.5 | $0.00008 | $0.00708 |
Grade A, and why
lead-project 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 9d 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 — 587 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead-Project — Autonomous Technical Lead
Drives a project from a stated intent to completion with minimal user involvement. The user provides commander's intent at startup and reviews at the end (or on andon cord). Between those points, the skill runs an OODA loop — observing project state, orienting against intent, deciding what to work on next, and acting by invoking other skills. It can scope new tickets, implement features, refactor, run reviews, hunt bugs, and deliberate on hard decisions. It stops autonomously when intent is fulfilled and quality is acceptable, or pulls the andon cord when it hits a wall.
Philosophy
This skill implements the autonomy discipline documented in references/autonomy.md at the highest level of the orchestrator family. The shared discipline governs the five levers (altitude rule, pre-loaded options, pre-rebutted recommendation, commander's intent, risk budgets), the cascade rule, the shared handoff template, and the "log instead of escalate" pattern. Skill-specific extensions (the OODA loop structure, trajectory audits, mechanical termination gates) are layered on top of that shared discipline.
Commander's intent is the anchor
The user states intent once, in structured form, at startup. Every subsequent decision traces back to it. Intent has five parts:
- Purpose — why this iteration exists
- Key tasks — non-negotiable outcomes
- End state — concrete conditions defining "done"
- Constraints — hard limits (what not to touch, what not to use)
- Non-goals — explicit out-of-scope (prevents scope expansion)
This five-field schema is the canonical implementation of commander's intent referenced from references/autonomy.md. Other orchestrator-family skills (/implement-project, /lead-refactor, /lead-bug-hunt) use lighter variants — fewer fields because the work is more bounded — but /lead-project's purpose is the most open-ended, so it elicits the full schema.
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.
- 9d ago First seen · 587 lines · 82 tokens per session scan A 8a667887195a
lead-project is a skill published in the GitHub repository chrisallenlane/claude-swe-workflows (18 stars, last pushed 3mo ago), licensed MIT. It adds 82 tokens to every session and 7,079 once invoked, about $0.0004 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:release-notes
Generate release notes from git history.
afc:clean
Pipeline artifact cleanup and codebase hygiene.
afc:issue
Analyze GitHub issue — investigate bug reports, understand requirements, inspect issues.
afc:launch
Generate release artifacts — version bump, changelog, release tags.
afc:learner
Review and promote learned patterns to project rules.
afc:qa
Project quality audit — test confidence, error handling gaps, code health.