agent-sort
Skill8 starsChanged 3 months agoMITView on GitHub
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.
We split this skill into the rules it gives an agent
19 rules. 19 are common, 0 are distinctive, and 0 are very specific to this project.
19
Common
Most of the 12 edited versions we read keep these.
0
Distinctive
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
- Common: line 10
Use this skill when a repo needs a project-specific ECC surface instead of the default full install.
- Common: line 24
Use the current repository as the source of truth, not generic preferences
- Common: line 25
Every DAILY decision must cite concrete repo evidence
- Common: line 27
Do not install hooks, rules, or scripts that the current repo cannot use
- Common: line 28
Prefer ECC-native surfaces.
- Common: line 42
Use two buckets only:
- Common: line 45
should load every session for this repo
- Common: line 49
should remain reachable through search, router skill, or selective manual use
- Common: line 53
Use repo-local evidence before making any classification:
- Common: line 77
If parallel subagents are available, split the review into these passes:
- Common: line 92
If subagents are not available, run the same passes sequentially.
- Common: line 151
If the repo already uses selective installs, update that plan instead of creating another system.
- Common: line 155
If the project wants a searchable library surface, create:
- Common: line 165
Do not duplicate every skill body inside the router.
- Common: line 169
After the plan is applied, verify:
- Common: line 171
every DAILY file exists where expected
- Common: line 185
If the next step is interactive installation or repair, hand off to:
- Common: line 189
If the next step is overlap cleanup or catalog review, hand off to:
- Common: line 193
If the next step is broader context trimming, hand off to:
“Common” is measured: kept by at least 6 in 10 of the 12 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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:
- DAILY inventory
- LIBRARY inventory
- install plan
- verification report
- optional
skill-libraryrouter 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.modParallel Review Passes
If parallel subagents are available, split the review into these passes:
- Agents
- classify
agents/*
- classify
- Skills
- classify
skills/*
- classify
- Commands
- classify
commands/*
- classify
- Rules
- classify
rules/*
- classify
- Hooks and scripts
- classify hook surfaces, MCP health checks, helper scripts, and OS compatibility
- 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 only3. 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 gapsOther versions13 projects use a version of this.
Word for word · 1
- renepf/claude-skills★ 0100% same
Edited · 12
- affaan-m/ECC★ 246k100% same
- mturac/everything-openai-codex★ 8998% same
- Fmarzochi/EGC★ 6194% same
- ysyecust/everything-claude-code★ 44100% same
- ArogyaReddy/https-github.com-affaan-m-everything-claude-code1★ 2100% same
- niloykumarbarman/EVERYTHING-CLAUDE-CODE★ 1100% same
- pcoulbourne/everything-claude-code★ 1100% same
- SamuelNDCE/claude-super-skill-library★ 1100% same
- davidanthonyn/claude-skills★ 0100% same
- pankaj-mahaur/Agent-Daemon★ 099% same
2 more not listed
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Used alongsideProjects with it also use openclaw-persona-forge.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
TironFoxSkillopenclaw-persona-forge
为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡, 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill,可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于:微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词:龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。
Also in 3 projects that use this
In this repository273 other files it gives its agents.
- accessibilitySkill
- agent-architecture-auditSkill
- agent-evalSkill
- agent-harness-constructionSkill
- agentic-engineeringSkill
- agentic-osSkill
- agent-introspection-debuggingSkill
- agent-payment-x402Skill
- agent-self-evaluationSkill
- ai-first-engineeringSkill
- ai-regression-testingSkill
- android-clean-architectureSkill
- angular-developerSkill
- api-connector-builderSkill
- api-designSkill
- architecture-decision-recordsSkill
- article-writingSkill
- automation-audit-opsSkill
- autonomous-agent-harnessSkill
- autonomous-loopsSkill
- backend-patternsSkill
- benchmark-methodologySkill
- benchmark-optimization-loopSkill
- benchmarkSkill
- blender-motion-state-inspectionSkill
- blueprintSkill
- brand-discoverySkill
- brand-voiceSkill
- browser-qaSkill
- bun-runtimeSkill
- canary-watchSkill
- carrier-relationship-managementSkill
- cisco-ios-patternsSkill
- ckSkill
- claude-devfleetSkill
- clickhouse-ioSkill
- click-path-auditSkill
- codebase-onboardingSkill
- codehealth-mcpSkill
- code-tourSkill
- coding-standardsSkill
- competitive-platform-analysisSkill
- competitive-report-structureSkill
- compose-multiplatform-patternsSkill
- config-gcSkill
- configure-eccSkill
- connections-optimizerSkill
- content-engineSkill
- content-hash-cache-patternSkill
- context-budgetSkill
- continuous-agent-loopSkill
- contract-firstSkill
- cost-aware-llm-pipelineSkill
- cost-trackingSkill
- council-multi-modelSkill
- councilSkill
- cpp-coding-standardsSkill
- cpp-testingSkill
- crosspostSkill
- csharp-testingSkill
- The first 60 shown.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
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.

