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 athola/claude-night-market --skill onboardgit clone --depth 1 https://github.com/athola/claude-night-marketWrote 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/athola/claude-night-market/onboard)<a href="https://agentmods.dev/skills/athola/claude-night-market/onboard"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/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/athola/claude-night-market/onboard"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/onboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.00407 |
| Opus 5 | $0.00015 | $0.00204 |
| Sonnet 5 | $0.00006 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00041 |
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 9d 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
Guided Onboarding
Walk a new developer through the codebase in structured stages.
When NOT To Use
- Ad-hoc questions outside a staged path (use
gauntlet:challenge) - The knowledge base does not exist yet (use
gauntlet:extract)
Stages
| Stage | Focus | Categories | Difficulty |
|---|---|---|---|
| 1 | Big picture | architecture, data_flow | 1-2 |
| 2 | Core domain | business_logic | 2-3 |
| 3 | Interfaces | api_contract, data_flow | 3 |
| 4 | Patterns | pattern, dependency | 3-4 |
| 5 | Hardening | error_handling, business_logic | 4-5 |
Steps
- Load onboarding progress
- Show current stage and progress summary
- Present 5 challenges from current stage
- Enable hints on first attempt
- Track mastery (correct twice = mastered)
- Check advancement (80% across 10+ challenges)
- Report progress
Graduation
After stage 5, the developer enters the regular gauntlet. Answer history carries over.
Exit Criteria
- Onboarding progress persists across invocations: current stage and challenge count survive session restarts and are loaded at Step 1
- Advancement to the next stage requires 80% correct across 10+ challenges in the current stage; partial completion does not advance
- Mastery tracking requires correct answers twice for a given challenge before it is marked mastered
- After Stage 5 completion, the developer's answer history carries over into the regular gauntlet challenge pool without loss
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.
- 9d ago First seen · 54 lines · 29 tokens per session scan A 0bac8c99aa2b
onboard is a skill published in the GitHub repository athola/claude-night-market (337 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 407 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 2026-09-03.
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