dependencies

dependencies is a command for coding agents from ramdhavepreetam/NervaPack. It costs 0 tokens per session (920 once invoked), scanned A, original, MIT.

A command that maps which source files import one another in a software project. It can also find circular import chains and show the dependency map as an interactive web page.

In plain words
What is it for?
It analyzes a whole project or one file, identifies heavily depended-on files and dependency layers, detects cycles, and saves an HTML visualization.
Why use it?
It makes hidden file relationships and dependency cycles easier to inspect without re-parsing the project or using an AI model.

Command

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 commands/ramdhavepreetam/nervapack/dependencies
Clone the repo
git clone --depth 1 https://github.com/ramdhavepreetam/NervaPack

Wrote 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.

agentmods badge for dependencies

README.md
[![agentmods](https://agentmods.dev/badge/commands/ramdhavepreetam/nervapack/dependencies.svg)](https://agentmods.dev/commands/ramdhavepreetam/nervapack/dependencies)
Your own site
<a href="https://agentmods.dev/commands/ramdhavepreetam/nervapack/dependencies"><img src="https://agentmods.dev/badge/commands/ramdhavepreetam/nervapack/dependencies.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 920 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 $0.00000 $0.00920
Opus 5 $0.00000 $0.00460
Sonnet 5 $0.00000 $0.00184
Haiku 4.5 $0.00000 $0.00092

Measured 4d ago against content hash 693b20d51f58, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dependencies 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 4d 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.

docs/user-guide/commands/dependencies.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

nervapack dependencies

Analyze file-level import dependencies, detect circular dependencies, and visualize the dependency graph.


Synopsis

nervapack dependencies [FILE] [OPTIONS]

Description

dependencies reads the import edges already stored in your NervaPack graph to build a file-level dependency map. It detects circular import chains, ranks files by how heavily they're depended on, and produces an interactive HTML visualization with the same physics engine used by nervapack visualize.

No re-parsing or LLM calls are required — it operates entirely on the existing graph.


Arguments and Options

Argument / Option Default Description
FILE (none) Analyze a single file instead of the whole project
--cycles / --no-cycles cycles on Include circular dependency detection
--layers / --no-layers layers on Include topological layer analysis
--output PATH .nervapack/dependencies.html Where to save the visualization
--no-browser off Generate without opening the browser

Examples

Full project analysis

nervapack dependencies

Single file — who does it import, who imports it?

nervapack dependencies src/graph/builder.py

Skip cycle detection (faster on very large graphs)

nervapack dependencies --no-cycles

Output — Project Analysis

╭──────────  Dependency Metrics  ──────────╮
│ Total Files              │  127          │
│ Total Dependencies       │  456          │
│ Max Dependency Depth     │  8            │
│ Orphan Files             │  3            │
╰──────────────────────────────────────────╯

⚠  Circular Dependencies Detected: 2 cycle(s)

Cycle 1:
  auth.py
  → user.py
  → session.py
  → auth.py  (back to start)

Cycle 2:
  config.py
  → settings.py
  → config.py  (back to start)

Most Depended-On Files (top 10):
  1. src/utils/common.py          (42 dependents)
  2. src/models/base.py           (38 dependents)
  3. src/config.py                (31 dependents)
  ...

Files With Most Dependencies (top 10):
  1. src/cli.py                   (18 imports)
  2. src/graph/builder.py         (14 imports)
  ...

Visualization saved to .nervapack/dependencies.html

Read the full file on GitHub · 139 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. 4d ago First seen · 139 lines · 0 tokens per session scan A 693b20d51f58

Subscribe to this mod's changes

dependencies is a command published in the GitHub repository ramdhavepreetam/NervaPack (1 stars, last pushed 11d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 920 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.