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/swingerman/engineer/onboardnpx skills add swingerman/engineer --skill onboardgit clone --depth 1 https://github.com/swingerman/engineerWhat 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 | $0.00064 | $0.05212 |
| Opus 5 | $0.00032 | $0.02606 |
| Sonnet 5 | $0.00013 | $0.01042 |
| Haiku 4.5 | $0.00006 | $0.00521 |
Grade A, and why
onboard 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
onboard
Checkpoint 0 — the DAE adoption ceremony. Establishes the charter, manifest, storage layout, and tracker. Project-scope, run once. Every other DAE skill depends on what it produces.
The goal. Onboarding a project to DAE succeeds when there is a clear path to full ATDD coverage of every feature — existing and new. A new feature is born covered by going through the pipeline. An existing feature is covered retroactively.
Onboarding is discovery and goal-setting — not the ATDD adoption itself. It discovers what's there (documented and undocumented), triages it by importance, assigns each feature a status, and produces a consolidation backlog. Bringing any one feature to full ATDD coverage is a follow-up task per feature — bounded, automatable, and a good candidate for remote-agent dispatch. Onboarding sets the path; it does not walk it.
A feature is fully ATDD-covered when its folder has feature.md, acs.md, spec.md (+ .build/spec.json IR), and generated acceptance tests that pass against the code.
When to use
- No
.engineer/manifest.yml→ full onboard (Steps 1–11) - Manifest exists → gap-check mode (validate, report gaps, don't re-onboard)
Not for: starting a feature (discuss / feature-init, after onboard); changing an existing charter (edit it directly, PR'd).
Human-decision checkpoints
Onboarding is a ceremony, not a mechanical scaffold. Three of its outputs are design decisions reserved for the human — the agent drafts, the human decides:
- The charter (Step 3) — architecture, conventions, scope, quality and autonomy stance.
- The tracking decision (Step 5) — which tracker the project uses.
- The roadmap decision (Step 5b) — which platform hosts the strategic roadmap, and (if one already exists) how it's migrated in. Strategy is a human call, like the charter.
Pre-filling from an existing codebase is encouraged. Rubber-stamping is not. Onboarding does NOT complete until the human has explicitly signed off on the charter and chosen the tracker and roadmap host — exactly as plan does for architecture (agent proposes, human confirms before proceeding). If the human is not available to decide, stop and emit a handoff with human_action_needed: decision — do not auto-decide and move on.
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 · 140 lines · 64 tokens per session scan A b3553ea2636a
onboard is a skill published in the GitHub repository swingerman/engineer (144 stars, last pushed 6d ago), licensed MIT. It adds 64 tokens to every session and 5,212 once invoked, about $0.0003 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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