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 dependency-analyzergit 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/dependency-analyzer)<a href="https://agentmods.dev/skills/matteocervelli/llms/dependency-analyzer"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/dependency-analyzer/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/dependency-analyzer"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/dependency-analyzer.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 | $0.00018 | $0.02709 |
| Opus 5.5 | $0.00007 | $0.01084 |
| Sonnet 5.5 | $0.00004 | $0.00542 |
| Haiku 4.5 | $0.00002 | $0.00271 |
Grade A, and why
dependency-analyzer 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dependency Analyzer Skill
Purpose
The Dependency Analyzer skill provides comprehensive dependency analysis capabilities for Python projects. It parses dependency configuration files (requirements.txt, pyproject.toml), builds dependency trees, detects version conflicts, and checks compatibility constraints.
Key Functions:
- Parse and analyze current project dependencies
- Identify new dependencies required for features
- Build visual dependency trees
- Detect version conflicts and incompatibilities
- Check compatibility across Python versions
- Generate structured dependency reports
When to Use
Use this skill when you need to:
- Analyze current project dependencies before adding new features
- Identify all dependencies required for a new feature implementation
- Detect version conflicts between dependencies
- Build dependency trees to understand package relationships
- Verify compatibility of new dependencies with existing ones
- Generate dependency reports for documentation
Typical Scenarios:
- Phase 2 design (dependency analysis for PRP)
- Pre-implementation dependency planning
- Dependency upgrade planning
- Conflict resolution
- Security vulnerability assessment (dependency version analysis)
Workflow
1. Parse Current Dependencies
Action: Read and parse all dependency configuration files in the project
# Check for requirements.txt
if [ -f requirements.txt ]; then
echo "Found requirements.txt"
cat requirements.txt
fi
# Check for pyproject.toml
if [ -f pyproject.toml ]; then
echo "Found pyproject.toml"
grep -A 30 "dependencies\|requires" pyproject.toml
fi
# Check for setup.py
if [ -f setup.py ]; then
echo "Found setup.py"
grep -A 20 "install_requires\|extras_require" setup.py
fi
Output: Inventory of current dependencies with versions
2. Build Dependency Tree
Action: Use dependency-checker script to build complete dependency tree
python .claude/skills/dependency-analyzer/dependency-checker-script.py \
--analyze \
--project-root . \
--output-format tree
What ships with it
2 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 · 400 lines · 18 tokens per session scan A 477d68ddff4e
dependency-analyzer is a skill published in the GitHub repository matteocervelli/llms (25 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 2,709 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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