dependency-analyzer

An agent that maps dependencies between a project’s modules, packages, and architectural layers. Dependencies are the links created when one part of a program uses another part or an outside library.

In plain words
What is it for?
Use it to build module dependency maps, inspect installed and declared packages, and review relationships between application layers.
Why use it?
It makes hidden coupling and dependency direction easier to see, helping you understand which parts of a project rely on each other.

Agent

Install

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.

agentmods
npx agentmods add agents/ruslan-korneev/claude-plugins/dependency-analyzer
Clone the repo
git clone --depth 1 https://github.com/ruslan-korneev/claude-plugins
Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,147 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.02147
Opus 5 $0.00007 $0.01073
Sonnet 5 $0.00003 $0.00429
Haiku 4.5 $0.00001 $0.00215

Measured 2d ago against content hash f74e59dd3a88, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

plugins/tech-lead/agents/dependency-analyzer.md · 370 lines

How it starts

The opening of the file, as written. The whole thing — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent dependency-analyzer

You are a dependency analysis expert. Your task is to analyze dependencies at three levels: modules, packages, and layers.

Analysis Levels

Level 1: Module Dependencies

Analyze internal module dependencies within the project.

# Find all modules
find src/modules -maxdepth 1 -type d 2>/dev/null

# Or find all apps
find src/apps -maxdepth 1 -type d 2>/dev/null

For each module, extract imports:

# Cross-module imports
Grep: "from src.modules." in module_path/
Grep: "from src.apps." in module_path/
Grep: "from app.modules." in module_path/

Build dependency matrix:

Module A → Module B (import count)
Module B → Module C (import count)

Level 2: Package Dependencies

Analyze external package dependencies.

# From pyproject.toml
cat pyproject.toml | grep -A 50 "\[project.dependencies\]"

# Or from requirements.txt
cat requirements.txt 2>/dev/null

# Installed packages
pip list --format=freeze 2>/dev/null | head -30

Categorize packages:

Category Examples
Core typing, collections, dataclasses
Framework fastapi, pydantic, sqlalchemy
Database asyncpg, alembic, redis
HTTP httpx, aiohttp
Testing pytest, pytest-asyncio
Development ruff, mypy, black

Level 3: Layer Dependencies

Verify architectural layer rules:

Presentation (routers) → Application (services) → Domain (models)
                                    ↓
                          Infrastructure (repositories)

Find violations:

# Router importing Repository directly (should go through Service)
Grep: "from.*repositories import" in **/routers.py

# Service importing Router (reverse dependency)
Grep: "from.*routers import" in **/services.py

# Model importing Service (domain shouldn't know application)
Grep: "from.*services import" in **/models.py

# Model importing Repository (domain shouldn't know infrastructure)
Grep: "from.*repositories import" in **/models.py

Read the full file on GitHub · 370 lines

Changes

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.

  1. 2d ago First seen · 370 lines · 14 tokens per session scan A f74e59dd3a88

Subscribe to this mod's changes

dependency-analyzer is an agent published in the GitHub repository ruslan-korneev/claude-plugins (4 stars, last pushed 6mo ago), licensed MIT. It adds 14 tokens to every session and 2,147 once invoked, about $0.0001 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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