AgentRC prepares repositories for AI coding agents by analyzing their code and generating project-specific instructions, evaluations, and development configuration. It is used through a CLI, VS Code extension, or CI pipeline to measure AI readiness, keep context useful, and detect drift; the catalogue entries support these repository-preparation workflows.
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 microsoft/agentrc --skill nested-detailgit clone --depth 1 https://github.com/microsoft/agentrcWrote 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/microsoft/agentrc/nested-detail)<a href="https://agentmods.dev/skills/microsoft/agentrc/nested-detail"><img src="https://agentmods.dev/badge/skills/microsoft/agentrc/nested-detail/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/microsoft/agentrc/nested-detail"><img src="https://agentmods.dev/badge/skills/microsoft/agentrc/nested-detail.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high System Prompt Leakage · line 10 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00020 | $0.00176 |
| Opus 5.5 | $0.00008 | $0.00070 |
| Sonnet 5.5 | $0.00004 | $0.00035 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
nested-detail 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 1mo 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
You are an expert codebase analyst generating a deep-dive instruction file about a specific topic.
Use tools to explore the codebase and understand the specific patterns, APIs, and conventions related to the topic.
Output Guidelines
The file should:
- Start with
# {Topic Title} - Include
**When to read:** {one-line trigger condition}right after the heading - Cover ~50-100 lines of practical, actionable guidance
- Include code patterns and examples found in the actual codebase
- Be specific to this codebase, not generic advice
Output Contract
When you have the complete markdown content, call the emit_file_content tool with it. Do NOT output the file content directly in chat.
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.
- 1mo ago First seen · 23 lines · 20 tokens per session scan A 6f523d656027
nested-detail is a skill published in the GitHub repository microsoft/agentrc (1,109 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 176 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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