Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Maximumsoft-Co-LTD/claude-flightdecknpx agentmods add skills/maximumsoft-co-ltd/claude-flightdeck/onboardWrote 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/maximumsoft-co-ltd/claude-flightdeck/onboard)<a href="https://agentmods.dev/skills/maximumsoft-co-ltd/claude-flightdeck/onboard"><img src="https://agentmods.dev/badge/skills/maximumsoft-co-ltd/claude-flightdeck/onboard.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 | $0.00152 | $0.02424 |
| Opus 5 | $0.00076 | $0.01212 |
| Sonnet 5 | $0.00030 | $0.00485 |
| Haiku 4.5 | $0.00015 | $0.00242 |
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 6d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/onboard — Generate the project-understanding docs
Announce: Using /onboard to generate the architecture + conventions docs.
Purpose. Bring the orchestrator and every dispatched agent from "template installed" to "understands THIS project" — by auto-generating, from the codebase, the three things the agents actually read:
| Output | What it is | Who reads it |
|---|---|---|
docs/setup/codebase-orientation.md |
the architecture map (structure, areas, stack, integrations, build/test) | orchestrator + agents (pre-task ritual) |
.claude/rules/code-style.md |
the conventions reference (layout, naming, error handling, test + framework idioms) | backend-engineer / frontend-engineer |
CLAUDE.md (root) + area CLAUDE.md |
routing + non-negotiables, drafted from the two above | orchestrator + agents |
Mostly automated (read-only Explore agents + one drafting agent) — minutes, not
hours. The deep human interview is opt-in (/onboard interview), not required.
Token budget
- Stages 0-2 are Bash (topology) + read-only Explore dispatches — no full file
Reads in the main session; miners stage their output to
_onboard-staging/. - Stage 3 drafting is delegated to
onboarding-engineer— trust its summary, don't re-Read the drafts. Hard cap: ~30k main-session tokens for the automated path (the old interview path cost far more).
Modes
/onboard— auto-generate the understanding docs (Stage 0→3 below). Default./onboard refresh— re-run the generation; present DELTA only (skip stages whose inputs are unchanged)./onboard interview— OPTIONAL deep human enrichment for context only humans have (system purpose, what's fragile, exemplary files, sprint state). See §Interview./onboard rules— re-mine git history for A-rule candidates + ratify them (operator-gated). See §Ratify./onboard retro— after the first sprint closes, reflect on the wizard itself.
Stage 0 — Pre-flight (auto)
What ships with it
8 files 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.
- references/draft-templates.md 12 KB
- references/interview-questions.md 8.9 KB
- references/multi-repo-coordination.md 9.5 KB
- references/pattern-mining-prompts.md 12 KB
- references/repo-topology-detection.md 8.6 KB
- scripts/detect-topology.sh 8.4 KB runs code
- scripts/extract-pr-comments.sh 2.7 KB runs code
- scripts/mine-git-history.sh 4.9 KB runs code
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.
- 6d ago First seen · 177 lines · 152 tokens per session scan A 9e1c61fa3c07
onboard is a skill published in the GitHub repository Maximumsoft-Co-LTD/claude-flightdeck (2 stars, last pushed 3mo ago), licensed MIT. It adds 152 tokens to every session and 2,424 once invoked, about $0.0008 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.
Other skills, from other repositories
issue-triage
3-phase issue backlog management with audit, deep analysis, and validated triage actions. Use when triaging GitHub issues, sorting bug reports, cleaning up stale tickets, or detecting duplicate issues. Args: 'all' to analyze all, issue numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit only.
cross-campaign
Discover and reference other camps, projects, and files across camp boundaries. Use when the user mentions another camp or campaign by name, references work done "in another project/camp", or needs to find/copy/compare code across camps.
review-pr
Perform a comprehensive code review of a pull request.
talk-stage5-script
Produces a complete 5-act pitch with speaker notes, a slide-by-slide specification, and a ready-to-paste Kimi prompt for AI slide generation. Requires validated angle and title from Stage 4. Use when you have a confirmed talk angle and need the full script, slide spec, and AI-generated presentation prompt.
guide-recap
Transform CHANGELOG entries into social content (LinkedIn, Twitter/X, Newsletter, Slack) in FR + EN. Use after releases or weekly to generate release notes, announcements, social media posts, or recap summaries from guide updates.
release-notes-generator
Generate release notes in 3 formats (CHANGELOG.md, PR body, Slack announcement) from git commits. Automatically categorizes changes and converts technical language to user-friendly messaging. Use for releases, changelogs, version notes, what's new summaries, or ship announcements.