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fallow

Skill1 starsChanged 31 days agoMITView on GitHub

Instructions for the upstream workflow: Static analysis for JS/TS codebases through the external Fallow CLI — health score with hotspots, dead code, semantic duplication, circular dependencies, PR risk from a diff, and JSON export, plus the Python companion and the combined audit script. Use when auditing a JS/TS project. Fallow is a third-party Rust binary: treat its report as an input to an audit, not as a proof on its own. Not for Python structural analysis — use the code_* detectors; not for the coding rules themselves — use code-rules.

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SKILL.md

Fallow — JS/TS codebase intelligence

Package scope and prerequisites

This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.

Instructions for a separately installed external JS/TS analysis CLI.

Purpose

How to run the external analyser on a JS/TS tree and how to read its score bands (A healthy through F critical), for the same family of questions the local code_* detectors answer for Python.

The full upstream commands, score table and pitfalls are in RULES.md, which is not bundled. Read the installed Fallow version's help and upstream policy before using its results; do not invent missing rules.

Boundaries

  • It is a third-party binary installed separately; its availability is not guaranteed by this repository.
  • Its findings have the same status as any detector output: an input to review, never a substitute for the evidence a change actually works.

When NOT to use

  • The tree is Python — use code_complexity, code_duplication, code_state and code_wrappers.
  • You want the coding standards — use code-rules.

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