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Get Started Free →Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.
.claude/skills/agent-sort/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | — | — |
| case-19 | ✗→✓ | ▲ Improved | — | — |
| case-05 | ✗→✓ | ▲ Improved | — | — |
| case-04 | ✗→✓ | ▲ Improved | — | — |
| case-08 | ✗→✓ | ▲ Improved | — | — |
Use this skill when a repo needs a project-specific ECC surface instead of the default full install.
The goal is not to guess what "feels useful." The goal is to classify ECC components with evidence from the actual codebase.
Produce these artifacts in order:
skill-library router if the project wants oneUse two buckets only:
DAILYLIBRARYUse repo-local evidence before making any classification:
Useful commands include:
bashrg --files rg -n "typescript|react|next|supabase|django|spring|flutter|swift" cat package.json cat pyproject.toml cat Cargo.toml cat pubspec.yaml cat go.mod
If parallel subagents are available, split the review into these passes:
agents/*skills/*commands/*rules/*If subagents are not available, run the same passes sequentially.
Establish the real stack before classifying anything:
For every candidate surface, record:
Use this format:
textskills/frontend-patterns | skill | DAILY | 84 .tsx files, next.config.ts present | core frontend stack skills/django-patterns | skill | LIBRARY | no .py files, no pyproject.toml | not active in this repo rules/typescript/* | rules | DAILY | package.json + tsconfig.json | active TS repo rules/python/* | rules | LIBRARY | zero Python source files | keep accessible only
Promote to DAILY when:
Demote to LIBRARY when:
Translate the classification into action:
.claude/skills/skill-libraryIf the repo already uses selective installs, update that plan instead of creating another system.
If the project wants a searchable library surface, create:
.claude/skills/skill-library/SKILL.mdThat router should contain:
Do not duplicate every skill body inside the router.
After the plan is applied, verify:
Return a compact report with:
If the next step is interactive installation or repair, hand off to:
configure-eccIf the next step is overlap cleanup or catalog review, hand off to:
skill-stocktakeIf the next step is broader context trimming, hand off to:
strategic-compactReturn the result in this order:
textSTACK - language/framework/runtime summary DAILY - always-loaded items with evidence LIBRARY - searchable/reference items with evidence INSTALL PLAN - what should be installed, removed, or routed VERIFICATION - checks run and remaining gaps
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-09 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 18 counted toward the lift figure. The other 4 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +55 percentage points is the difference between those two pass rates over the 18 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.