Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add geniro-io/geniro-claude-harness/plugin install geniroWrote 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/geniro-io/geniro-claude-harness/onboard)<a href="https://agentmods.dev/skills/geniro-io/geniro-claude-harness/onboard"><img src="https://agentmods.dev/badge/skills/geniro-io/geniro-claude-harness/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/geniro-io/geniro-claude-harness/onboard"><img src="https://agentmods.dev/badge/skills/geniro-io/geniro-claude-harness/onboard.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00062 | $0.05619 |
| Opus 5 | $0.00031 | $0.02809 |
| Sonnet 5 | $0.00012 | $0.01124 |
| Haiku 4.5 | $0.00006 | $0.00562 |
Grade C, and why
onboard scanned grade C with 1 finding 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 12d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf .geniro/state/onboard/<slug>/ 2>/dev/null || true This is a copy
94% identical to geniro-onboard — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboard: rapid codebase orientation
Contents
- Arguments
- Outputs — the 8-section
_CODEBASE_MAP.mdtemplate - State machine
- Loop invariants
- Anti-rationalization
- Quality-first budgets
- ACI per-phase tool surface
- Definition of done
- Phase 1 — Discover
- Phase 2 — Map
- State file schema
2-phase loop (Discover → Map). Generates a structured map that serves as a reference for the session.
Runtime portability. ${CLAUDE_PLUGIN_ROOT} is a path placeholder Claude Code substitutes into file references, never a shell export — it reads empty in a Bash call under every host, Claude Code included, so an empty probe is no evidence of another runtime (CLAUDECODE in the environment marks Claude Code). Resolve the root by working these in order: the ancestor directory of this file containing .claude-plugin/plugin.json; a copy of the referenced file sitting beside this one (the Cursor build ships each skill's own phase and reference files there); a plugin checkout inside the workspace. Substitute the resolved root for every ${CLAUDE_PLUGIN_ROOT} occurrence and export it as CLAUDE_PLUGIN_ROOT in every Bash call. Work the rungs with a command, not a judgment: the run's first Bash call lists the directory this file was read from and each candidate root, and its output is echoed verbatim before anything else. Read the rungs against that output — a path it does not show did not resolve, and a file it does not show cannot be read, however confidently a later step would report otherwise. A ladder that resolves is bookkeeping, not a finding: keep the echo to the probe output and the resolved root, and reserve a degraded-run notice for a rung that actually failed. Read ${CLAUDE_PLUGIN_ROOT}/skills/_shared/runtime-portability.md before deciding a step cannot run here: it substitutes mechanisms, not steps, and routes a host with no one to ask to ${CLAUDE_PLUGIN_ROOT}/skills/_shared/non-interactive-host.md. When no rung resolves, the files are missing but the contract is not — open your first message by naming what is unavailable, run every phase and gate this skill declares, never let the project's own rules stand in for its decision gates, and take no outward-facing action (ready-for-review PR, merge, force-push, protected-branch push, posted comment, tracker transition) without an explicit answer.
What ships with it
1 file 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.
- 12d ago First seen · 300 lines · 62 tokens per session scan C 4bdb6963fd0d
onboard is a skill published in the GitHub repository geniro-io/geniro-claude-harness (8 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 5,619 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). It is 94% identical to geniro-onboard, differing in 14 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…