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Rule refactor

Skill event4u-app/agent-config/dist/agent-src/skills/rule-refactor

Universal AI Agent OS — audited skills, governance rules, replayable state. One contract, every host agent.

Install
npx -y skills add event4u-app/agent-config --skill rule-refactor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when the rule set is over the Augment budget, when a new rule would breach it, or when asked to audit / merge / prune rules — runs the audit pipeline and proposes a verdict per rule.

SKILL.md

5.3 KB, as published. Nobody here has run it

<!-- cloud_safe: degrade -->

rule-refactor

When to use

  • measure_augment_budget --check fails (utilisation ≥ 0.95)
  • A new rule would push the budget over 0.95 — caught by the budget gate in rule-writing
  • User says "audit rules", "rule cleanup", "rules over budget", "prune rules", "merge rules", "rule system review"
  • Periodic governance pass after a batch of rule additions

Do NOT use this skill for:

Iron Law

Threshold-lift is forbidden. When the budget breaches, the content must shrink — not the gate. Loosening FAIL_THRESHOLD in scripts/measure_augment_budget.ts to make CI pass is an explicit anti-pattern. The only valid budget-growth move is an ADR that raises TOTAL_CAP.

Procedure

1. Inspect the current budget state

./scripts-run src/scripts/measure_augment_budget --json > /tmp/budget-before.json
./scripts-run src/scripts/measure_rule_budget --json > /tmp/rule-budget-before.json

2. Run the audit pipeline

The audit infrastructure already exists — compose it:

./scripts-run src/scripts/audit_auto_rules      # → agents/runtime/reports/auto-rules-audit.{json,md}
./scripts-run src/scripts/audit_overlap         # → appends overlap pairs to the MD
./scripts-run src/scripts/audit_likelihood      # → agents/runtime/reports/auto-rules-likelihood.json

Then read agents/runtime/reports/auto-rules-audit.md end-to-end.

3. Categorise every flagged rule

For each rule the audit surfaces (overlap pair, low-likelihood, oversized, or the new addition that triggered this skill), assign exactly one verdict:

VerdictTest
keepIron-Law / always-on safety net, no overlap, fires often
merge≥ 2 rules same domain, near-identical triggers, overlap ≥ 0.4
deleteNever fires (low-likelihood + no path/keyword hit in 30 days), or fully subsumed by a skill
move-to-contextBody is reference material (tables, mechanics, examples) — the obligation is short, the rest is lookup
promote-to-skillBody has numbered steps / a workflow — not a constraint

4. Present the verdict table to the user

One Markdown table, one row per flagged rule, before any file change. User approves the list. No silent edits.

5. Apply approved changes

For each approved verdict:

  • merge → rewrite the surviving rule to cover both domains; delete the absorbed one; update any routes_to: references.
  • delete → remove the file from .agent-src.uncondensed/rules/ and the corresponding dist/agent-src/rules/ projection.
  • move-to-context → extract the body into .agent-src.uncondensed/contexts/<area>/<name>.md, replace the rule body with the obligation + a load_context: pointer.
  • promote-to-skill → create .agent-src.uncondensed/skills/<name>/SKILL.md, replace the rule with an auto-trigger stub that routes to it (or delete the rule entirely if the skill's own trigger suffices).

6. Re-validate

bash scripts/condense.sh --sync
./scripts-run src/scripts/condense --generate-tools
./scripts-run src/scripts/measure_augment_budget --check   # must exit 0
./scripts-run src/scripts/skill_linter --all               # 0 FAIL

Then run your package's full CI pipeline (see Taskfile.yml for the canonical sequence) before pushing.

7. Record the delta

Append a snapshot to agents/.augment-budget-history.jsonl:

./scripts-run src/scripts/measure_augment_budget --trend-append

Commit the cleanup as a separate chunk from any rule-add commits so the history shows "added X" + "cleaned up Y" as distinct steps.

Output format

  1. Verdict table (approved by user) at the top of the cleanup PR description
  2. Per-verdict commits (one per merge / delete / move / promote group)
  3. Final measure_augment_budget --check output showing utilisation < 0.95
  4. Trend snapshot recorded

Gotchas

  • Do NOT raise FAIL_THRESHOLD to dodge the audit
  • Do NOT delete a rule that has a routes_to: pointer without updating the pointer's source
  • Do NOT merge rules across tier boundaries (e.g. tier-1 always with a tier-3 stub) without surfacing the tier collapse to the user
  • Do NOT skip the trend-append — the history is what tells future agents how the cap was managed

Do NOT

  • Do NOT loosen the budget gate
  • Do NOT touch the cap (TOTAL_CAP) without an ADR
  • Do NOT apply changes before user approves the verdict table
  • Do NOT delete the rule-refactor audit reports — they're the artifact reviewers cite

Cloud Behavior

On cloud surfaces, the audit scripts are not reachable. The skill still applies — prose-only:

  • Inspect the rule list (frontmatter + descriptions) and propose the verdict table from reading alone.
  • Tell the user to run the audit scripts locally before applying.
  • Do not attempt to call any script.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.