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/luisfelipemoro/harness-devkit/analysisnpx skills add LuisFelipeMoro/Harness-devkit --skill analysisgit clone --depth 1 https://github.com/LuisFelipeMoro/Harness-devkitWhat 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 | $0.00038 | $0.00463 |
| Opus 5 | $0.00019 | $0.00231 |
| Sonnet 5 | $0.00008 | $0.00093 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
analysis 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 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.
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
Run the analysis phase (Analyst + PM only). If no task is provided, ask first.
Load agent files on demand — never pre-load both at once. Use references/output-format.md section headers for all agent output.
Scope: requirements analysis only — no architecture decisions, no Language column, no sub-task decomposition. To create an execution plan from this output, run
/planning. To implement end-to-end (includes planning), run/multi-agent.
Step 1 — Analyst (Mary)
Load agents/analyst.md. Run against the task description.
- Include: language context, security constraints, business goals
- Output:
docs/deliveries/{key}/product-brief.md(show in full) — derive the slug + key from the feature name perreferences/delivery-and-worktree.md; a root-levelproduct-brief.mdwould be clobbered by the next delivery
Step 2 — PM (John)
Load agents/pm.md. Run against the Brief from Step 1.
- Security ACs are mandatory for any I/O, auth, or data-handling epic
- Output:
docs/deliveries/{key}/PRD.md(show in full)
Step 3 — Epic Summary
Extract every epic from the PRD and display the Epic Summary:
| Epic | Tasks | Acceptance Criteria | Security ACs |
|---|---|---|---|
| Epic N: {title} | T{N}.1: {imperative}, T{N}.2: … | AC1, AC2, … | SEC-1, … (or —) |
After showing the summary, print the closing block from references/output-contract.md.
Machine-checkable behavior contract: skill.spec.yml · dependency ledger: deps.toml (both generated by the skillspec CLI and git-ignored — Claude never loads them).
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 · 49 lines · 38 tokens per session scan A 11e5ad041ec2
analysis is a skill published in the GitHub repository LuisFelipeMoro/Harness-devkit (10 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 463 once invoked, about $0.0002 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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