Agent助手
- 作者仓库星标 188,749
- 作者更新于 实时读取
- 作者仓库 ECC
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @affaan-m · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 即装即用
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- Python
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agent-sort
description: Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules…
category: AI 智能
runtime: Python
---
# agent-sort 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“When to Use / Non-Negotiable Rules / Outputs”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“When to Use / Non-Negotiable Rules / Outputs”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
先用一个小任务确认它会围绕“When to Use / Non-Negotiable Rules / Outputs”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: agent-sort
description: Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules…
category: AI 智能
source: affaan-m/ECC
---
# agent-sort
## 什么时候使用
- 用于审阅代码、文档或方案并给出可执行反馈 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;通常不需要…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「When to Use / Non-Negotiable Rules / Outputs」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "agent-sort" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> When to Use / Non-Negotiable Rules / Outputs
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Python | 读取文件、写入/修改文件 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} 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.mod
Parallel 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 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
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核