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Agent Sort

  • 1.4k installs
  • 238k repo stars
  • Updated August 5, 2026
  • affaan-m/ecc

This is a copy of agent-sort by affaan-m - installs and ranking accrue to the original listing.

agent-sort is a Claude Code skill that generates a lean, repo-specific ECC surface by sorting skills, rules, and hooks into DAILY versus LIBRARY buckets for developers who want evidence-backed ECC installs instead of the

About

agent-sort is an ECC skill that builds an evidence-backed install plan for a specific repository by classifying ECC components with parallel repo-aware review passes. Instead of guessing what feels useful, agent-sort sorts skills, commands, rules, hooks, and extras into DAILY buckets for everyday use and LIBRARY buckets for occasional reference based on signals from the actual codebase. Developers use agent-sort when full ECC installs are too noisy, the repo stack is known, but nobody wants to manually audit dozens of skills and rules. The output is a trimmed ECC surface that loads only what the project needs, reducing agent context bloat and conflicting guidance. It pairs naturally with configure-ecc for installation after the sort plan is approved, and suits monorepos or polyglot projects where only a subset of ECC domains applies.

  • Parallel repo-aware review passes that classify every ECC component
  • Evidence-backed decisions using concrete grep results from the current repository
  • Separates always-loaded DAILY workflow surfaces from searchable LIBRARY surfaces
  • Outputs two clean inventories: DAILY inventory followed by LIBRARY inventory
  • Prevents noisy full-bundle installs while keeping unused items accessible

Agent Sort by the numbers

  • 1,407 all-time installs (skills.sh)
  • +88 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/affaan-m/ecc --skill agent-sort

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Listed on Skillselion
Installs1.4k
repo stars238k
Last updatedAugust 5, 2026
Repositoryaffaan-m/ecc

How do you trim ECC to only needed skills?

Generate a lean, repo-specific ECC surface that loads only the skills, rules, and hooks actually needed by their codebase.

Who is it for?

Developers adopting ECC on a specific repo who want a lean, codebase-evidence install instead of the full skill bundle.

Skip if: Greenfield projects with no codebase signals yet or teams happy loading the complete ECC catalog without curation.

When should I use this skill?

User wants a project-specific ECC subset, says full ECC is too noisy, or needs repo-aware skill and rule sorting.

What you get

Evidence-backed ECC install plan with DAILY and LIBRARY component buckets tailored to the repository stack.

  • ECC install plan
  • DAILY component list
  • LIBRARY component list

Files

SKILL.mdMarkdownGitHub ↗

Agent Sort

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.

When to Use

  • A project only needs a subset of ECC and full installs are too noisy
  • The repo stack is clear, but nobody wants to hand-curate skills one by one
  • A team wants a repeatable install decision backed by grep evidence instead of opinion
  • You need to separate always-loaded daily workflow surfaces from searchable library/reference surfaces
  • A repo has drifted into the wrong language, rule, or hook set and needs cleanup

Non-Negotiable Rules

  • Use the current repository as the source of truth, not generic preferences
  • Every DAILY decision must cite concrete repo evidence
  • LIBRARY does not mean "delete"; it means "keep accessible without loading by default"
  • Do not install hooks, rules, or scripts that the current repo cannot use
  • Prefer ECC-native surfaces; do not introduce a second install system

Outputs

Produce these artifacts in order:

1. DAILY inventory 2. LIBRARY inventory 3. install plan 4. verification report 5. optional skill-library router if the project wants one

Classification Model

Use two buckets only:

  • DAILY
  • should load every session for this repo
  • strongly matched to the repo's language, framework, workflow, or operator surface
  • LIBRARY
  • useful to retain, but not worth loading by default
  • should remain reachable through search, router skill, or selective manual use

Evidence Sources

Use repo-local evidence before making any classification:

  • file extensions
  • package managers and lockfiles
  • framework configs
  • CI and hook configs
  • build/test scripts
  • imports and dependency manifests
  • repo docs that explicitly describe the stack

Useful commands include:

rg --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

Parallel Review Passes

If parallel subagents are available, split the review into these passes:

1. Agents

  • classify agents/*

2. Skills

  • classify skills/*

3. Commands

  • classify commands/*

4. Rules

  • classify rules/*

5. Hooks and scripts

  • classify hook surfaces, MCP health checks, helper scripts, and OS compatibility

6. Extras

  • classify contexts, examples, MCP configs, templates, and guidance docs

If subagents are not available, run the same passes sequentially.

Core Workflow

1. Read the repo

Establish the real stack before classifying anything:

  • languages in use
  • frameworks in use
  • primary package manager
  • test stack
  • lint/format stack
  • deployment/runtime surface
  • operator integrations already present

2. Build the evidence table

For every candidate surface, record:

  • component path
  • component type
  • proposed bucket
  • repo evidence
  • short justification

Use this format:

skills/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

3. Decide DAILY vs LIBRARY

Promote to DAILY when:

  • the repo clearly uses the matching stack
  • the component is general enough to help every session
  • the repo already depends on the corresponding runtime or workflow

Demote to LIBRARY when:

  • the component is off-stack
  • the repo might need it later, but not every day
  • it adds context overhead without immediate relevance

4. Build the install plan

Translate the classification into action:

  • DAILY skills -> install or keep in .claude/skills/
  • DAILY commands -> keep as explicit shims only if still useful
  • DAILY rules -> install only matching language sets
  • DAILY hooks/scripts -> keep only compatible ones
  • LIBRARY surfaces -> keep accessible through search or skill-library

If the repo already uses selective installs, update that plan instead of creating another system.

5. Create the optional library router

If the project wants a searchable library surface, create:

  • .claude/skills/skill-library/SKILL.md

That router should contain:

  • a short explanation of DAILY vs LIBRARY
  • grouped trigger keywords
  • where the library references live

Do not duplicate every skill body inside the router.

6. Verify the result

After the plan is applied, verify:

  • every DAILY file exists where expected
  • stale language rules were not left active
  • incompatible hooks were not installed
  • the resulting install actually matches the repo stack

Return a compact report with:

  • DAILY count
  • LIBRARY count
  • removed stale surfaces
  • open questions

Handoffs

If the next step is interactive installation or repair, hand off to:

  • configure-ecc

If the next step is overlap cleanup or catalog review, hand off to:

  • skill-stocktake

If the next step is broader context trimming, hand off to:

  • strategic-compact

Output Format

Return the result in this order:

STACK
- 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

Related skills

How it compares

Pick agent-sort before configure-ecc when you need codebase-evidence curation of which ECC components to install rather than selecting from the full catalog manually.

FAQ

What buckets does agent-sort create?

agent-sort classifies ECC skills, commands, rules, hooks, and extras into DAILY buckets for everyday use and LIBRARY buckets for occasional reference, based on evidence from parallel repo-aware review passes.

When should agent-sort run instead of a full ECC install?

agent-sort should run when a project only needs a subset of ECC and full installs add noise. The skill produces an evidence-backed plan so agents load only stack-relevant components.

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