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 commands/intense-visions/harness-engineering/craft-fleetgit clone --depth 1 https://github.com/Intense-Visions/harness-engineeringWrote 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/commands/intense-visions/harness-engineering/craft-fleet)<a href="https://agentmods.dev/commands/intense-visions/harness-engineering/craft-fleet"><img src="https://agentmods.dev/badge/commands/intense-visions/harness-engineering/craft-fleet.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 | $0.00144 | $0.00966 |
| Opus 5 | $0.00072 | $0.00483 |
| Sonnet 5 | $0.00029 | $0.00193 |
| Haiku 4.5 | $0.00014 | $0.00097 |
Grade A, and why
harness:craft-fleet 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 5d 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.
What it actually says
Phases:
- select: Compose the enabled craft skills over the repository, fold their findings into (scope, craft domain) targets, apply the noise floor, cross-check each target against open elevation PRs and already-filed quality items, route every surviving finding elevate or file or route by the mechanical boundary and then re-form the targets by verdict so a split scope yields at most one elevate target and at most one file item each carrying only its own findings, enforce the caps in emitted items rather than findings, and order by tier times impact with roadmap-pilot impact scoring
- confirm: Present the enabled craft domains, the ranked targets with their elevate and file split, a taste-calibration sample of verbatim findings, the noise floor, the per-batch caps, the proposed concurrency, and the pinned base SHA for a single up-front human approval that may disable domains or re-tune the floor
- dispatch: Fan out worktree-isolated subagents, one per confirmed elevate target, each running the real harness-refactoring pipeline over that target's cited findings and pushing a branch carrying its step-granular commit trail; a target that needs a structural change or whose baseline is not clean at the pinned base — a red suite or a failing harness validate or check-deps — downgrades itself to file and reports, and no subagent runs a re-critique
- verify: For every elevation independently confirm critique provenance for each changed location, the step-granular refactoring commit trail, and net improvement via a two-run re-critique executed here rather than read from the subagent, plus behavior preservation and all-OS CI green; for every filing, which has no branch, confirm the narrower verified-filing standard of critique provenance plus the cross-check that the target is not already addressed — never by subagent self-report
- file-and-report: Open one elevation PR per verified target and craft domain without merging, file every verified and every downgraded item as a roadmap item carrying its cite and rubric and location plus an assumptions-made note the orchestrator writes here from the SELECT routing basis, convert every elevation slot to a filed item under --file-only, park routed correctness and security findings for hand-back, and emit a one-row-per-item batch summary including noise-floor drops, over-cap counts, downgrade reasons, cross-check drops, and quiet targets
<execution_context> @agents/skills/claude-code/craft-fleet/SKILL.md @agents/skills/claude-code/craft-fleet/skill.yaml </execution_context>
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.
- 5d ago First seen · 41 lines · 144 tokens per session scan A c86ae95f96b8
harness:craft-fleet is a command published in the GitHub repository Intense-Visions/harness-engineering (20 stars, last pushed today), licensed MIT. It adds 144 tokens to every session and 966 once invoked, about $0.0007 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.