Borrowing it
Nothing to install: this file belongs to lsampaioweb/ai-instructions. 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/lsampaioweb/ai-instructions/main/.cursor/skills/review-ai-customization-files/SKILL.mdgit clone --depth 1 https://github.com/lsampaioweb/ai-instructionsWrote 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/lsampaioweb/ai-instructions/review-ai-customization-files)<a href="https://agentmods.dev/skills/lsampaioweb/ai-instructions/review-ai-customization-files"><img src="https://agentmods.dev/badge/skills/lsampaioweb/ai-instructions/review-ai-customization-files/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/lsampaioweb/ai-instructions/review-ai-customization-files"><img src="https://agentmods.dev/badge/skills/lsampaioweb/ai-instructions/review-ai-customization-files.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 | $0.00059 | $0.00859 |
| Opus 5 | $0.00030 | $0.00430 |
| Sonnet 5 | $0.00012 | $0.00172 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
review-ai-customization-files 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Customization Audit Engine
- Obey
AGENTS.md(project root). - Read-only audit; edit only user-approved items after explicit approval; leave non-targeted text unchanged.
- Load style baseline (first match):
.cursor/rules/ai-customization.mdc→.github/instructions/ai-customization.instructions.md→ ask.
1. Scope & Analysis
- Target only user-provided scope. If missing, stop and request inputs.
- Load and parse the applicable style baseline for the current scope.
- Establish active cross-file references across target directories.
2. Resolution Rules
- Scanning Rigor: Scan 100% of files in scope.
- Audit Checklist: Inspect every file along six dimensions:
- Duplicate rules (intra-file and cross-file).
- Conflicting rules (direct and soft conflicts — including overlapping
applyTo/globs/pathswith contradictory verbs). - Verbosity (filler and low-signal prose).
- Directives (ambiguous or non-enforceable phrasing).
- Frontmatter (routing patterns, discoverability).
- Token efficiency (density; reward high-signal literals; penalize descriptive bloat).
- Scoring Protocol: Score each file 0–10. Assign 0–2 per dimension with factual justification. Map dimensions as follows: Clarity = frontmatter + token efficiency (2 checklist items → 1 column), Enforceability = directives, Consistency = cross-file alignment, Brevity = verbosity, Conflict-Free = duplicates + conflicts (2 checklist items → 1 column).
- Status Classification: PASS (9–10) | WARN (7–8) | FAIL (0–6).
3. Safety Guards
- Never sample; partial coverage invalidates the audit.
- Execution Boundary: Read-only audit. Do not edit files or execute mutations until explicit user confirmation.
- Fix Application Rule: If authorized, modify only approved items. Non-targeted text remains unchanged.
4. Review Plan Layout
Use this exact markdown schema:
Scope
- Files scanned:
- Assumptions applied:
Findings (Ordered by Severity: Critical | High | Medium | Low)
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.
- 11d ago First seen · 86 lines · 59 tokens per session scan A 8a74432ebeda
review-ai-customization-files is a skill published in the GitHub repository lsampaioweb/ai-instructions (1 stars, last pushed 19d ago), licensed MIT. It adds 59 tokens to every session and 859 once invoked, about $0.0003 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 2026-08-31.
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