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 VKirill/claude-lane-stack --skill project-onboardgit clone --depth 1 https://github.com/VKirill/claude-lane-stackWrote 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/vkirill/claude-lane-stack/project-onboard)<a href="https://agentmods.dev/skills/vkirill/claude-lane-stack/project-onboard"><img src="https://agentmods.dev/badge/skills/vkirill/claude-lane-stack/project-onboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vkirill/claude-lane-stack/project-onboard"><img src="https://agentmods.dev/badge/skills/vkirill/claude-lane-stack/project-onboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00000 | $0.01371 |
| Opus 5 | $0.00000 | $0.00685 |
| Sonnet 5 | $0.00000 | $0.00274 |
| Haiku 4.5 | $0.00000 | $0.00137 |
Grade A, and why
project-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 3d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project onboard (Claude Lane Stack)
Info (print and stop)
If $ARGUMENTS is info, or the user says info / справка / как запускать this skill:
print the block below verbatim (Russian), then stop. Do not start onboard.
project-onboard — первичная карта репо (CLAUDE.md + LLM-pack)
Когда
- Нет CLAUDE.md / пустой или чужой репо.
- Уже живой UI без DESIGN.md → design-lead (project-design), не повторный onboard.
Как открыть шпаргалку
- /lane-stack:project-onboard info
- каталог: /lane-stack:info
Запуск
- /project-onboard
- /project-onboard deep
- /project-onboard /path/to/repo fast
- CLI: project-onboard .
- агент: project-onboarder (Codex, не Grok)
Флаги
- deep / fast — глубина
- full / minimal — scenario
- --seed-only — только заглушки, без модели
После
- RU-саммари: поверхности, модули, тесты, DESIGN?, RUNBOOK?
- has_ui → docs/DESIGN.md (Google)
- docs включены + паспорт тонкий → сначала этот скилл / project-onboarder, потом docs-maintainer
- weekly refresh: docs-maintainer, не этот скилл
Who runs it
| Role | How |
|---|---|
| One-shot CLI | project-onboard . (detect + seed + Codex/Cursor fill) |
| Default writer | Codex (stages.onboard from adoc) |
| Instructions | ~/.agents/codex/instructions/onboard.md |
| Model / effort / fast | adoc stages.onboard |
| Weekly refresh | docs-maintainer (ONBOARD_REFRESH=weekly) |
| Existing UI, no DESIGN.md | design-lead (skill project-design) — extract, do not re-onboard |
Default CLI = full pipeline. --seed-only = stubs without model. Do not use Grok.
References (MUST load before filling)
| Ref | What |
|---|---|
| references/PACK-SCHEMAS.md | Author every file (Diátaxis + schemas) |
| references/VALIDATION.md | Shell + acceptance; refuse complete |
| references/design-md-standard.md | Full @google/design.md canon |
| https://diataxis.fr/ | Tutorial / how-to / reference / explanation |
| https://agents.md/ · https://llmstxt.org/ | Agent entry + curated index |
What ships with it
3 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.
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.
- 3d ago Changed · +2 lines a6f8d55bc1af
- 9d ago First seen · 123 lines · 0 tokens per session scan A 18006dcb8970
project-onboard is a skill published in the GitHub repository VKirill/claude-lane-stack (115 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,371 tokens. 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 skills, from other repositories
afc:release-notes
Generate release notes from git history.
afc:clean
Pipeline artifact cleanup and codebase hygiene.
afc:issue
Analyze GitHub issue — investigate bug reports, understand requirements, inspect issues.
afc:launch
Generate release artifacts — version bump, changelog, release tags.
afc:learner
Review and promote learned patterns to project rules.
afc:qa
Project quality audit — test confidence, error handling gaps, code health.