recursive-dep-trace

Trace static dependency closures of code entry points into markdown.

7|1|Updated Apr 1, 2026
One-click install
npx skills add https://github.com/gyy0592/claude-config --skill recursive-dep-trace
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: recursive-dep-trace
Source: https://github.com/gyy0592/claude-config/tree/main/skills/recursive-dep-trace
Command: npx skills add https://github.com/gyy0592/claude-config --skill recursive-dep-trace

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill produces a line-precise, reproducibility-focused audit of everything an entry script touches so a developer can determine exactly what is required to run that script from an empty machine. It replaces guesswork with a live, resumable markdown trace that proves which files, data assets, and third-party libraries are needed and where unresolved gaps remain.

Core Features & Use Cases

  • Live, incremental trace: writes a stream-of-consciousness markdown file that is updated after every small read step so another agent can resume at the exact file:line and TODO stack state.
  • Recursive static closure: reads every file to EOF and pushes every referenced file/path onto a TODO stack until the closure ends in third-party packages, public resources, or provable BLOCKED items.
  • Data-file inspection: opens and inspects bundled data files (.npz, .pkl, .json, .yaml, .csv) to extract embedded path strings and continue tracing them.
  • Robust BLOCKED handling: applies three distinct exhaustive search strategies before marking a reference blocked, logs commands verbatim, and performs a second-pass retry before user escalation.
  • Use cases: preparing a repository for open-source release, extracting minimal reproducible examples, auditing training/inference pipelines, and verifying that a project can be run from a cold machine.

Quick Start

Trace recursive dependencies for train.py and produce a live incremental markdown trace at artifacts/task_recursive-dep-trace/train_trace.zh.md.

Frequently Asked Questions about recursive-dep-trace

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I trace static dependencies of a Python script without executing the code?

Static dependency tracing reads source files line-by-line to EOF, pushing every referenced file onto a TODO stack until the closure ends in third-party packages or provable BLOCKED items. This produces a reproducible markdown trace without executing target code.

Can I extract a minimal reproducible example from a repository by auditing its training pipeline?

Auditing a training pipeline via recursive static closure identifies exactly which files and data assets an entry script touches. This replaces guesswork, proving what is required to run the script from an empty machine for a minimal reproducible example.

How does recursive dependency tracing handle bundled data files like .npz or .pkl?

Recursive dependency tracing opens and inspects bundled data files including .npz, .pkl, .json, .yaml, and .csv. It extracts embedded path strings from these artifacts and continues tracing them recursively within the static dependency closure.

What is the best way to prepare a repository for open-source release and verify cold machine reproducibility?

Preparing a repository for open-source release requires a line-precise audit of everything an entry script touches. A live incremental markdown trace proves which files, data assets, and third-party libraries are needed to run from a cold machine.

What happens when a dependency trace encounters unresolved or blocked references?

When encountering unresolved references, robust BLOCKED handling applies three distinct exhaustive search strategies before marking a reference blocked. It logs commands verbatim and performs a second-pass retry before escalating to the user.

Does recursive dependency tracing support resuming an interrupted code audit?

Recursive dependency tracing supports resuming interrupted code audits through a live incremental markdown file. Updated after every read step, it allows another agent to resume at the exact file:line and TODO stack state.