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Agent Skill · 研究检索

gather-plan-apply(聚集计划申请)

gather-plan-apply 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

gather-plan-apply 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 42,992。

总安装 1,023周安装 41GitHub Stars 6下载 331核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:gather-plan-apply(聚集计划申请)
来源仓库:https://github.com/mgd34msu/goodvibes-plugin
仓库路径:skills/gather-plan-apply
安装命令:
npx skills add https://github.com/mgd34msu/goodvibes-plugin --skill gather-plan-apply
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mgd34msu/goodvibes-plugin --skill gather-plan-apply

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

gather-plan-apply 采用 G-P-A 三阶段模式:收集、计划、应用,优化信息处理流程。适用于 Codex、Claude 等平台中批量读取关键文件并执行精准编辑。通过 GitHub 安装,遵循每阶段每种工具仅调用一次的规范。需合理拆分任务批次以提高效率,避免单次过载。

输出结果需经人工复核,尤其涉及代码修改时。

来源仓库内路径:skills/gather-plan-apply

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/mgd34msu/goodvibes-plugin --skill gather-plan-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

gather-plan-apply 怎么安装?

在终端执行 npx skills add https://github.com/mgd34msu/goodvibes-plugin --skill gather-plan-apply。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

gather-plan-apply 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

gather-plan-apply 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

gather-plan-apply 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

gather-plan-apply 用的人多吗?

公开数据是累计安装 1,023 次,近一周安装 41 次,下载 331 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

gather-plan-apply 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
gather-plan-apply

聚集计划申请 · 本页

1,0236需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Resources

scripts/
  validate-gpa-compliance.sh
references/
  examples-and-checklists.md

Gather-Plan-Apply Protocol (GPA Workflow)

The GPA loop enforces a one-call-per-tool-type-per-phase workflow that eliminates token waste from excessive tool calls. This is NOT a suggestion — it is a MANDATORY execution pattern for all GoodVibes agents.

THE EXACT WORKFLOW

0. LOAD SKILLS (once, before any GPA cycle)
   - Call get_skill_content for role-relevant skills
   - This is NOT part of the GPA cycle itself

1. G — GATHER (1-2 tool calls)
   - Check .goodvibes/memory/ files FIRST (failures, patterns, decisions)
   - Single `discover` call with ALL queries batched inside
   - Multiple query types (glob, grep, symbols, structural) in one call
   - Can search file content via grep/symbols queries
   - Batch any file reads that need full content alongside discover
   - Output: files_only or locations (minimal verbosity)

2. P — PLAN (0 tool calls, cognitive only)
   - Agent thinks about what it learned from GATHER
   - Plans which files to create/write/edit
   - Plans which commands to run for validation
   - Identifies ALL batch opportunities — same-type ops go in one call
   - Plans the EXACT apply call structure

3. A — APPLY (1-2 tool calls)
   - Writes and edits batched into one precision_write or precision_edit call
   - Validation commands batched into one precision_exec call
   - Key: one call per tool type, everything batched inside it

4. LOOP — Back to G if:
   - Results didn't match expectations
   - Scope changed
   - Validation failed

CALL BUDGET PER CYCLE

PhaseTool CallsTypePurpose
G (Gather)1-2discover + optional precision_readAll discovery + memory reads
P (Plan)0CognitivePlan apply operations
A (Apply)1-2precision_write/precision_edit + precision_execAll writes/edits + validation
TOTAL2-4

Core rule: One call per tool type per phase. Never make two precision_read calls in the same phase — batch both files into the one call.

Note on sequential calls: Sequential calls are acceptable when operations depend on each other (e.g., write then verify). Always prefer true batching via internal precision tool arrays (files array, edits array, commands array).

KEY RULES (NON-NEGOTIABLE)

  1. discover batches ALL discovery queries into 1 call — NEVER use separate precision_glob, precision_grep for discovery
  2. Plan steps produce ZERO tool calls — they are cognitive (agent thinks in text)
  3. One call per tool type per phase — if you need 3 files read, batch them in 1 precision_read call
  4. APPLY output = 1-2 calls — precision_write/edit for files, precision_exec for commands
  5. ToolSearch is NOT part of GPA — load tools once at start, don't search mid-cycle
  6. Check memory FIRST — always read.goodvibes/memory/ before implementing

Phase 1: GATHER (1-2 calls)

Initial Setup: Check Memory

Before discovering files, check what's already known. Batch memory reads with your discover call or as a separate read:

# GOOD: Memory reads batched with file content reads
precision_read:
  files:
    - path: ".goodvibes/memory/failures.json"
    - path: ".goodvibes/memory/patterns.json"
    - path: ".goodvibes/memory/decisions.json"
  verbosity: minimal

The discover Tool

The discover tool runs multiple grep/glob/symbols/structural queries in parallel, returning results keyed by query ID. This is your primary discovery mechanism.

Pattern: Batch ALL discovery queries

# GOOD: 1 discover call with everything
discover:
  queries:
    - id: existing_files
      type: glob
      patterns: ["src/features/auth/**/*.ts"]
    - id: existing_patterns
      type: grep
      pattern: "export (function|const|class)"
      glob: "src/features/**/*.ts"
    - id: exported_hooks
      type: symbols
      query: "use"
      kinds: ["function"]
    - id: console_logs
      type: structural
      structural_pattern: "console.log($$$ARGS)"
  verbosity: files_only

Query types:

  • glob - Find files by path patterns
  • grep - Find files containing patterns
  • symbols - Find exported functions/types/classes
  • structural - Find AST patterns (e.g., function calls)

Output modes:

  • count_only - Just counts (scope estimation)
  • files_only - File paths only (building target lists) ← USE THIS
  • locations - File paths + line numbers (when you need exact locations)

Reading Full File Contents

For reading full file contents, use precision_read in the GATHER phase, batched with memory reads or as a second call if discover results are needed first.

[BAD] vs [GOOD] Gather Patterns

[BAD] — Sequential discovery queries (multiple tool calls)

# BAD: 4 separate tool calls for discovery
precision_glob:
  patterns: ["src/**/*.ts"]

precision_grep:
  queries:
    - id: exports
      pattern: "export function"

precision_read:
  files:
    - path: ".goodvibes/memory/failures.json"

precision_grep:
  queries:
    - id: imports
      pattern: "import.*from"

[GOOD] — Single discover call + batched memory reads (2 tool calls)

# GOOD: 1 discover call with all queries
discover:
  queries:
    - id: files
      type: glob
      patterns: ["src/**/*.ts"]
    - id: exports
      type: grep
      pattern: "export function"
      glob: "src/**/*.ts"
    - id: imports
      type: grep
      pattern: "import.*from"
      glob: "src/**/*.ts"
  verbosity: files_only

# GOOD: Memory reads in one batched call
precision_read:
  files:
    - path: ".goodvibes/memory/failures.json"
    - path: ".goodvibes/memory/patterns.json"
    - path: ".goodvibes/memory/decisions.json"
  verbosity: minimal

Phase 2: PLAN (0 calls, cognitive only)

Purpose

Planning is cognitive work, not tool calls. You think in text about:

  • Which files to create/write
  • Which files to edit (with exact find/replace)
  • Which commands to run for validation
  • ALL batch opportunities — same-type ops must be batched

Output: A written plan with NO tool calls

Plan Structure

Plan:
1. Create the following files:
   - src/features/auth/types.ts — User interface
   - src/features/auth/hooks.ts — useAuth hook
   - src/features/auth/index.ts — barrel export

2. Edit the following files:
   - src/app/layout.tsx — wrap App with AuthProvider

3. Validate:
   - npm run typecheck (expect exit 0)
   - npm run lint (expect exit 0)

4. Batch plan:
   - Call 1 (Apply): precision_write with 3 files + precision_edit with 1 edit
   - Call 2 (Apply): precision_exec with 2 commands

[BAD] vs [GOOD] Planning

[BAD] — Vague plan that leads to sequential calls

Plan:
- Create some files
- Maybe edit layout
- Run typecheck

This leads to:

precision_write: ...   # 1st call
precision_write: ...   # 2nd call! (should be batched)
precision_edit: ...    # 3rd call! (could combine with above pattern)

[GOOD] — Specific plan with exact batch structure

Plan:
1. Write 3 files in 1 precision_write call:
   - src/features/auth/types.ts (symbols)
   - src/features/auth/hooks.ts (content)
   - src/features/auth/index.ts (content)

2. Edit 1 file in 1 precision_edit call:
   - src/app/layout.tsx — wrap with AuthProvider

3. Validate in 1 precision_exec call:
   - npm run typecheck
   - npm run lint

Phase 3: APPLY (1-2 calls)

Pattern: Batch All Writes/Edits

Single precision_write with multiple files:

precision_write:
  files:
    - path: "src/features/auth/types.ts"
      content: |
        export interface User {
          id: string;
          email: string;
        }
    - path: "src/features/auth/hooks.ts"
      content: |
        import type { User } from './types';
        export function useAuth(): User | null { /*...*/ }
    - path: "src/features/auth/index.ts"
      content: |
        export * from './types';
        export * from './hooks';
  verbosity: count_only

OR single precision_edit with multiple edits:

precision_edit:
  edits:
    - path: "src/app/layout.tsx"
      find: "<App />"
      replace: "<AuthProvider><App /></AuthProvider>"
    - path: "src/middleware.ts"
      find: "export const config = {}"
      replace: "export const config = { matcher: ['/dashboard/:path*'] }"
    - path: "src/lib/api.ts"
      find: "headers: {}"
      replace: "headers: { Authorization: `Bearer ${token}` }"
  verbosity: minimal

Validation via precision_exec (second Apply call):

precision_exec:
  commands:
    - cmd: "npm run typecheck"
      expect:
        exit_code: 0
    - cmd: "npm run lint"
      expect:
        exit_code: 0
  verbosity: minimal

[BAD] vs [GOOD] Apply Batching

[BAD] — 3 separate precision_write calls

precision_write:
  files:
    - path: "file1.ts"
      content: "..."

precision_write:  # Second call!
  files:
    - path: "file2.ts"
      content: "..."

precision_write:  # Third call!
  files:
    - path: "file3.ts"
      content: "..."

[GOOD] — 1 precision_write call with 3 files

precision_write:
  files:
    - path: "file1.ts"
      content: "..."
    - path: "file2.ts"
      content: "..."
    - path: "file3.ts"
      content: "..."
  verbosity: count_only

Phase 4: LOOP (When to Return to Gather)

Loop Triggers

  1. Results don't match expectations — Typecheck fails, tests fail, unexpected behavior
  2. Scope changed — Discovery revealed different situation than expected
  3. New information — Task requirements clarified during execution

Loop Pattern

# Initial GPA cycle
discover: ...          # Gather call 1
precision_read: ...    # Gather call 2 (memory + key files)
precision_write: ...   # Apply call 1
precision_exec: ...    # Apply call 2 — FAILS typecheck

# LOOP: Start new GPA cycle with refined discovery
discover:              # Gather call 1 (new cycle)
  queries:
    - id: find_missing_import
      type: grep
      pattern: "export.*User"
      glob: "src/**/*.ts"
  verbosity: locations  # Need exact location

precision_edit: ...    # Apply call 1 (new cycle) - fix the issue
precision_exec: ...    # Apply call 2 (new cycle) - re-validate

Complete Example: Implementing Auth Feature

Cycle 1: Initial Implementation

Step 1 — GATHER (2 calls)

# Call 1: Check memory
precision_read:
  files:
    - path: ".goodvibes/memory/failures.json"
    - path: ".goodvibes/memory/decisions.json"
  verbosity: minimal

# Call 2: Discover landscape
discover:
  queries:
    - id: existing_auth
      type: glob
      patterns: ["src/features/auth/**/*.ts", "src/**/auth*.ts"]
    - id: auth_patterns
      type: grep
      pattern: "(useAuth|getSession|AuthProvider)"
      glob: "src/**/*.{ts,tsx}"
    - id: user_types
      type: symbols
      query: "User"
      kinds: ["interface", "type"]
  verbosity: files_only

Step 2 — PLAN (0 calls, cognitive)

Gather results:
- No memory failures for auth
- No existing auth files
- No auth patterns in use
- User type exists in src/types/user.ts

Plan:
Apply Call 1 (precision_write): Create 3 auth files
Apply Call 2 (precision_exec): typecheck + lint

Step 3 — APPLY (2 calls)

# Call 1: Create files
precision_write:
  files:
    - path: "src/features/auth/provider.tsx"
      content: |
        import { ClerkProvider } from '@clerk/nextjs';
        export function AuthProvider({ children }: { children: React.ReactNode }) {
          return <ClerkProvider>{children}</ClerkProvider>;
        }
    - path: "src/features/auth/hooks.ts"
      content: |
        import { useUser } from '@clerk/nextjs';
        import type { User } from '@/types/user';
        export function useAuth(): User | null {
          const { user } = useUser();
          if (!user) return null;
          return { id: user.id, email: user.emailAddresses[0].emailAddress, name: user.fullName };
        }
    - path: "src/features/auth/index.ts"
      content: |
        export { AuthProvider } from './provider';
        export { useAuth } from './hooks';
  verbosity: count_only

# Call 2: Validate
precision_exec:
  commands:
    - cmd: "npm run typecheck"
      expect:
        exit_code: 0
    - cmd: "npm run lint"
      expect:
        exit_code: 0
  verbosity: minimal

# Result: typecheck FAILS — missing @clerk/nextjs

Total calls in Cycle 1: 4 (precision_read + discover + precision_write + precision_exec)

Cycle 2: Fix Missing Dependency

Step 1 — GATHER (1 call)

discover:
  queries:
    - id: package_json
      type: glob
      patterns: ["package.json"]
    - id: clerk_usage
      type: grep
      pattern: "@clerk/nextjs"
      glob: "src/**/*.{ts,tsx}"
  verbosity: files_only

Step 2 — PLAN (0 calls, cognitive)

Discovery: @clerk/nextjs not in package.json
Plan:
Apply Call 1 (precision_exec): npm install @clerk/nextjs, then typecheck

Step 3 — APPLY (1 call)

precision_exec:
  commands:
    - cmd: "npm install @clerk/nextjs"
    - cmd: "npm run typecheck"
      expect:
        exit_code: 0
  verbosity: minimal

# Result: PASSES

Total calls in Cycle 2: 2 (discover + precision_exec)

Common Violations and Fixes

ViolationTool CallsFix
Sequential precision_read calls5+Batch all files into 1 precision_read call
Sequential precision_write calls5+Batch all files into 1 precision_write call
Using precision_glob + precision_grep separately2+Use 1 discover call with both query types
Reading outline, then content2Read content once if you'll need it
Planning via tool calls1+Plan in text (cognitive work = 0 calls)
Memory reads skipped-Always check.goodvibes/memory/ in Gather phase

Enforcement

If you find yourself making the same tool type twice in a phase, you are violating the protocol. Stop and restructure:

  1. Identify which calls are discovery → batch into 1 discover call
  2. Identify which calls are memory/file reads → batch into 1 precision_read call
  3. Identify which calls are writes/edits → batch into same-type calls (writes together, edits together)
  4. Ensure planning happens in text, not via tools

Target: one call per tool type per phase.

Summary

  • G (Gather): check memory + discover + optional precision_read for key files
  • P (Plan): 0 calls (cognitive)
  • A (Apply): precision_write/precision_edit + precision_exec for validation
  • LOOP: Start new cycle if needed

Rule: One call per tool type per phase. Maximize batching within each call.

Make this your default mode of operation.

平台分布

Codex

35.28%
按下载量换算117

Claude

28.18%
按下载量换算93

Cursor

19.54%
按下载量换算65

Gemini CLI

9.76%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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