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/large-file-refactor

@ccfca26
by Paul Bergpaulrberg/agent-skills94 stars
7

Discover large source-file refactor candidates and propose cohesion- and risk-driven split plans using available semantic tooling.

Use this Skill: https://skilld.dev/gh/paulrberg/agent-skills/large-file-refactor

This session only. Nothing lands on disk.

SKILL.md

≈38 tokens always: the name and description. ≈877 when used: this file. ≈11 more on demand in 1 file.

Large File Refactor

This skill is coordination-exempt: skip the ai-coord gate for its declared work.

If these instructions are already present in the conversation from a slash or dollar invocation, follow them directly; do not invoke this skill again through a skill tool.

Use LOC thresholds to discover candidates, then decide whether a split is justified by cohesion, coupling, ownership, and change risk. Source files match above 1000 LOC; test files use a relaxed 2000 LOC discovery threshold.

Arguments

  • path: Optional file or directory to scan. Default: current working directory.
  • --include-generated: Include generated, vendored, dependency, and build-output paths that are skipped by default.

Workflow

  1. Resolve the skill directory, then run the helper from the target repository:

    uv run "<skill-dir>/scripts/large-file-refactor.py" [path] [--include-generated]
  2. Preserve the helper's Markdown table as the exhaustive report. Do not omit matching rows, even when the refactor plan only covers a subset.

  3. If the helper reports no threshold matches, stop after the report. A match is a candidate, not proof that the file should be split.

  4. Draft a refactor plan for the 3 largest files only, unless the user explicitly requested another count.

  5. For each candidate, rank split value by mixed responsibilities, change frequency/risk, coupling, and testability. Use whichever semantic symbol/reference tooling is available; prefer Serena when installed:

    • Inspect symbol overviews, references, imports, and relevant history.
    • Use the evidence to choose extraction boundaries, target module names, migration order, and test coverage.
  6. Do not implement the refactor unless the user separately asks for execution.

Refactor Plan Format

For each selected file, include:

  • Current role: the file's apparent responsibility and why line count is a symptom.
  • Semantic pass: the exact symbol/reference/history inspection to run before moving code.
  • Split proposal: 2-5 target modules or files with responsibilities.
  • Migration order: small, reviewable steps that preserve public behavior.
  • Verification: narrow tests, type checks, builds, or smoke checks that prove the split.

Lead each plan with one explicit verdict: ### ✂ Split justified, ### 🧱 Keep intact, or ### ⚠️ Generated — change the generator. Use a compact evidence table for repeated criteria. When proposing a split, show the source and target modules as a tree only when it clarifies ownership.

If a selected file is generated or vendored because --include-generated was used, plan against the generator, schema, or upstream source instead of hand-splitting generated output.

Guard Rails

  • Treat the table as source of truth for size ranking only; rank refactor priority separately.
  • Keep the plan cohesive; do not split solely to reduce line count.
  • Prefer existing project module boundaries and naming conventions.
  • Call out when the helper used its portable LOC estimate instead of tokei.

Completion

Complete with the exhaustive threshold report plus evidence-ranked plans only for candidates whose cohesion or change risk justifies a split. Lead with ### 🔎 Large-file scan — <candidate count>, state when a large file should remain intact and why, and surface the portable-LOC fallback as ⚠️ Approximate counts when used. Keep the helper's exhaustive table, paths, LOC values, and commands exact and undecorated.

Source: SKILL.md on GitHub

No alertstoday3 checks · Risk SAFE
  • Gen Agent Trust Hubtoday

    The skill is safe to use and helps identify large source files for refactoring by using standard developer tools like git, tokei, and ripgrep. The only minor security concern is indirect prompt injection, which could occur if the source code files analyzed by the agent contain malicious instructions designed to mislead it.

  • Sockettoday

    No alerts

  • Snyktoday

    Risk: LOW · No issues

Signed by skilld at ccfca26. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated last week
argument-hint
[path] [--include-generated]
coordination
exempt
disable-model-invocation
true

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