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 matteocervelli/llms --skill analysisgit clone --depth 1 https://github.com/matteocervelli/llmsWrote 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/matteocervelli/llms/analysis)<a href="https://agentmods.dev/skills/matteocervelli/llms/analysis"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/analysis/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/matteocervelli/llms/analysis"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/analysis.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 | $0.00031 | $0.01108 |
| Opus 5.5 | $0.00012 | $0.00443 |
| Sonnet 5.5 | $0.00006 | $0.00222 |
| Haiku 4.5 | $0.00003 | $0.00111 |
Grade A, and why
analysis 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.
How it starts
The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Analysis Skill
Purpose
This skill provides systematic analysis of feature requirements from GitHub issues, evaluating technical feasibility, dependencies, security implications, and implementation scope.
When to Use
- Starting feature implementation from a GitHub issue
- Need to understand requirements and acceptance criteria
- Evaluating technical approach and dependencies
- Identifying security considerations early
- Scoping effort and potential risks
Analysis Workflow
1. Requirements Extraction
From GitHub Issue:
- Parse issue title, description, and acceptance criteria
- Extract functional and non-functional requirements
- Identify user stories and use cases
- Review issue comments for clarifications
- Check linked issues and dependencies
Deliverable: Structured requirements list with priorities
2. Technical Stack Evaluation
Assess Technology Fit:
- Review project's TECH-STACK.md for current technologies
- Identify required libraries/frameworks
- Check version compatibility
- Evaluate performance implications
- Consider maintenance burden
Tools to Use:
- Read TECH-STACK.md and relevant documentation
- Use
scripts/analyze_deps.pyfor dependency analysis - Grep codebase for similar patterns
Deliverable: Technology recommendations with rationale
3. Dependency Analysis
Identify Dependencies:
- External libraries (pip/npm/cargo packages)
- Internal modules and services
- Database schema changes
- API contracts
- Configuration requirements
Check for Conflicts:
# Use the analyze_deps script
python scripts/analyze_deps.py --feature <feature-name>
Deliverable: Dependency map with conflict analysis
4. Security Assessment
Review Security Implications:
- Authentication/authorization requirements
- Input validation needs
- Data sensitivity (PII, credentials, etc.)
- API security (rate limiting, CORS, etc.)
- Dependency vulnerabilities
Use Checklist:
Refer to security-checklist.md for systematic review
What ships with it
3 files 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.
- 1mo ago First seen · 204 lines · 31 tokens per session scan A d593678719c7
analysis is a skill published in the GitHub repository matteocervelli/llms (25 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 1,108 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 2026-09-01.
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