agentleFS
preetamnathpreetamnath/agent-skills/skills/tighten-file/SKILL.md

tighten-file

Skill4 starsChanged 7 months agoMITView on GitHub

File-level tightening pass on an instruction file (CLAUDE.md, skill, agent prompt, style guide) using `tighten-instruction` as the lens. TRIGGER when: user says 'tighten/simplify this file/skill/CLAUDE.md', 'cut this down', 'titan instruction on this file'; user points at a verbose instruction file and wants it leaner.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Keep load-bearing rationale.

    line 29
  2. Very specific:

    Write Nothing to tighten — already clear.

    line 46
  3. Distinctive:

    every Step 1 invariant survived.

    line 52
  4. Distinctive:

    every exact token and anchor remains valid.

    line 53
  5. Distinctive:

    every cross-reference still resolves.

    line 54
  6. Distinctive:

    no rationale lost its constraint.

    line 55

≈ “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

Tighten File

Apply tighten-instruction at three levels: whole file, section, instruction.

Steps

Step 0 — Load

Invoke the tighten-instruction skill via the Skill tool. This file-level workflow owns the apply gate.

Step 1 — Pin meaning

State the file's purpose in one line. List every distinct instruction or fact that must survive, including exact tokens, anchors, output contracts, and load-bearing rationale.

Step 2 — Find and score edits

Apply the loaded lens at whole-file, section, and instruction level. For each independent edit, record:

  • the current text;
  • the proposed text, or cut entirely;
  • the level: whole-file, section, or instruction;
  • confidence 0.00–1.00 that the edit improves clarity without changing meaning.

Keep load-bearing rationale. When a reason is the non-derivable fact, shape it as behaviour — constraint; do not cut it as explanation.

Step 3 — Gate and apply

Show the plan, then:

  • apply every edit at c ≥ 0.80;
  • hold lower-confidence proposals and leave their text unchanged;
  • apply whole-file and section edits before instruction edits;
  • drop any later proposal an applied edit dissolves.
**Tightening plan — <file>:**
- [0.92] section: <current> → <proposed>
- [0.61] instruction: <current> → <proposed> · held (< 0.80)

Write Nothing to tighten — already clear. when no edit qualifies.

Step 4 — Prove and report

Re-read the changed file cold. Confirm:

  • every Step 1 invariant survived;
  • every exact token and anchor remains valid;
  • every cross-reference still resolves;
  • no rationale lost its constraint.

Revert or fix any edit that fails this proof.

Report applied edits, held proposals, dissolved proposals, and net clauses, lines, and words removed.

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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.