agentleFS
aprameyakaprameyak/coding-skills/legacy-change/SKILL.md

legacy-change

Skill1 starsChanged 41 days agoMITView on GitHub

Change legacy code safely with characterization coverage. Use when editing poorly tested old modules, unknown systems, or brittle production paths.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer adapter/facade over rewriting the core.

    line 12
  2. Distinctive:

    Only then refactor within the covered seam.

    line 14
  3. Distinctive:

    Do not big-bang rewrite legacy modules for a small fix.

    line 18
  4. Distinctive:

    Avoid drive-by cleanups outside the seam.

    line 20
  5. Distinctive:

    If no test harness exists, add the thinnest possible one at the boundary.

    line 21

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Legacy Change

Process

  1. Find the smallest seam around the change.
  2. Characterize current behavior with tests or golden fixtures before editing.
  3. Prefer adapter/facade over rewriting the core.
  4. Make the behavior change in a thin step; keep characterization green.
  5. Only then refactor within the covered seam.

Rules

  • Do not big-bang rewrite legacy modules for a small fix.
  • Record discovered invariants in tests, not only in chat.
  • Avoid drive-by cleanups outside the seam.
  • If no test harness exists, add the thinnest possible one at the boundary.

Exit

  • Before-behavior captured
  • Intended change verified
  • Rollback path understood

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.