Borrowing it
Nothing to install: this file belongs to frankxai/Starlight-Intelligence-System. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/frankxai/Starlight-Intelligence-System/main/.grok/skills/repo-mastery/SKILL.mdgit clone --depth 1 https://github.com/frankxai/Starlight-Intelligence-SystemWrote 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/frankxai/starlight-intelligence-system/repo-mastery)<a href="https://agentmods.dev/skills/frankxai/starlight-intelligence-system/repo-mastery"><img src="https://agentmods.dev/badge/skills/frankxai/starlight-intelligence-system/repo-mastery/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/frankxai/starlight-intelligence-system/repo-mastery"><img src="https://agentmods.dev/badge/skills/frankxai/starlight-intelligence-system/repo-mastery.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 | $0.00101 | $0.00236 |
| Opus 5.5 | $0.00040 | $0.00094 |
| Sonnet 5.5 | $0.00020 | $0.00047 |
| Haiku 4.5 | $0.00010 | $0.00024 |
Grade A, and why
repo-mastery 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 27d 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.
This is a copy
100% identical to repo-mastery — 0 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.
What it actually says
Repo Mastery (Grok Edition)
Steps:
- Inventory + read rules (CLAUDE/AGENTS/GROK.md priority)
- Parallel subagents for ACOS core, SIP, products, mcp-servers, skills catalog
- Cross-ref with remote (gh/MCP) + local FS
- Map .grok + .claude compat, skills 100+, hooks, agents
- Apply gates (excellence-review) before any recs
- Structured output: components, critical paths, opportunities. No unrequested MDs.
Embody Frank DNA. Lead with builds.
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.
- 27d ago Changed · +101 tokens per session 839feacd6c4f
- 1mo ago First seen · 17 lines · 0 tokens per session scan A 8bbf38c9ea28
repo-mastery is a skill published in the GitHub repository frankxai/Starlight-Intelligence-System (11 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 236 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to repo-mastery, differing in 0 lines, and is treated as a copy.
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