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 gigsmart/haiku-method --skill haiku-adoptgit clone --depth 1 https://github.com/gigsmart/haiku-methodWrote 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/gigsmart/haiku-method/haiku-adopt)<a href="https://agentmods.dev/skills/gigsmart/haiku-method/haiku-adopt"><img src="https://agentmods.dev/badge/skills/gigsmart/haiku-method/haiku-adopt.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 5.1 | $0.00021 | $0.00347 |
| Opus 5 | $0.00010 | $0.00173 |
| Sonnet 5 | $0.00004 | $0.00069 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
haiku-adopt 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 7d 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
Adopt
Reverse-engineer an existing feature into H·AI·K·U intent artifacts.
Process
Phase 0 — Pre-checks
- Check for slug conflicts
Phase 1 — Gather description
- Get feature description
- Ask for code paths (specific directories or search whole repo)
- Ask for git references (PRs, branches, date range)
Phase 2 — Feature exploration (5 parallel subagents)
- Code path analysis (modules, entry points, dependencies)
- Git history analysis (commit groups, PR boundaries, timeline)
- Test analysis (test files, coverage patterns, verified behaviors)
- CI configuration analysis (pipelines, quality gates)
- Deployment surface analysis (containers, infra, monitoring)
Phase 3 — Propose intent and units (user confirms)
Phase 4 — Reverse-engineer success criteria from tests
Phase 5 — Generate operational plan (if operational surface found)
Phase 6 — Write artifacts (intent.md, unit files, discovery.md, operations/)
Phase 7 — Handoff (summary + next steps)
CRITICAL: MUST NOT modify existing code. Adopted units describe what already exists — they are written with synthetic terminal iterations[] (last entry result: "advance") and signed reviews{} / approvals{} so the cursor sees them as completed and never dispatches a hat against them. Forward-only invariant: completed work is immutable.
Wait for user confirmation at each gate (Phase 3, 4, 5).
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.
- 7d ago First seen · 35 lines · 21 tokens per session scan A ae0b47b46a1c
haiku-adopt is a skill published in the GitHub repository gigsmart/haiku-method (24 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 347 once invoked, about $0.0001 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.
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