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.
git clone --depth 1 https://github.com/mcqua007/agents-skeletonWrote 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/rules/mcqua007/agents-skeleton/example-scoped)<a href="https://agentmods.dev/rules/mcqua007/agents-skeleton/example-scoped"><img src="https://agentmods.dev/badge/rules/mcqua007/agents-skeleton/example-scoped/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/rules/mcqua007/agents-skeleton/example-scoped"><img src="https://agentmods.dev/badge/rules/mcqua007/agents-skeleton/example-scoped.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 | $0.00000 | $0.00115 |
| Opus 5.5 | $0.00000 | $0.00046 |
| Sonnet 5.5 | $0.00000 | $0.00023 |
| Haiku 4.5 | $0.00000 | $0.00012 |
Grade A, and why
example-scoped 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
Component Guidelines
- Components should be self-contained with clear props interfaces.
- Prefer composition over inheritance.
- Extract reusable logic into custom hooks or utility functions.
- Keep component files focused — one primary export per file.
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 · 16 lines · 0 tokens per session scan A 7ab7ef459034
example-scoped is a cursor rule published in the GitHub repository mcqua007/agents-skeleton (2 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 115 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 2026-08-31.
Other cursor rules, from other repositories
xiigen-no-secrets
Prevent publishing sensitive material. Use before commits, reports, examples, adaptation outputs, and release.
xiigen-claim-verification
Verify claims before presenting them as facts. Use in final answers, reports, reviews, and architecture decisions.
xiigen-code-examination
Understand local code before changing it. Use before implementation, refactoring, test fixes, or architecture changes.
xiigen-debug-session
Package debugging work so another agent or human can resume it. Use for longer debugging tasks or handoffs.
xiigen-root-cause-tracing
Find the cause behind a symptom. Use when a failure repeats, appears indirect, or has multiple possible causes.
xiigen-session-output-contract
Make session output useful, complete, and resumable. Use at handoff, final response, or long-running task summary.