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spec-kitty-tasks规格小猫任务

Agent Skill

spec-kitty-tasks 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。

总安装

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2

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181
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:spec-kitty-tasks(规格小猫任务)
来源仓库:https://github.com/richfrem/agent-plugins-skills
仓库路径:skills/spec-kitty-tasks
安装命令:
npx skills add https://github.com/richfrem/agent-plugins-skills --skill spec-kitty-tasks
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/richfrem/agent-plugins-skills --skill spec-kitty-tasks

简介

spec-kitty-tasks 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于需要根据关键词或任务场景进行信息检索和筛选的工作流。
  • 通过关键词输入和来源线索匹配,输出结构化候选结果列表。
  • 安装命令:npx skills add https://github.com/richfrem/agent-plugins-skills --skill spec-kitty-tasks
  • 建议确认权限范围和维护状态,注意可能触发联网或文件读写操作

SKILL.md

🔗 Workflow Provenance

Source: This skill augments the baseline workflow located at ./workflows/spec-kitty.tasks.md. It acts as an intelligent wrapper that is continuously improved with each execution.

/spec-kitty.tasks - Generate Work Packages

Version: 0.11.0+

⚠️ CRITICAL: THIS IS THE MOST IMPORTANT PLANNING WORK

You are creating the blueprint for implementation. The quality of work packages determines:

  • How easily agents can implement the feature
  • How parallelizable the work is
  • How reviewable the code will be
  • Whether the feature succeeds or fails

QUALITY OVER SPEED: This is NOT the time to save tokens or rush. Take your time to:

  • Understand the full scope deeply
  • Break work into clear, manageable pieces
  • Write detailed, actionable guidance
  • Think through risks and edge cases

Token usage is EXPECTED and GOOD here. A thorough task breakdown saves 10x the effort during implementation. Do not cut corners.


📍 WORKING DIRECTORY: Stay in the project root checkout

IMPORTANT: Tasks works in the project root checkout. NO worktrees created.

# Run from project root (same directory as /spec-kitty.plan):
# You should already be here if you just ran /spec-kitty.plan

# Creates:
# - kitty-specs/###-feature/tasks/WP01-*.md → In project root checkout
# - kitty-specs/###-feature/tasks/WP02-*.md → In project root checkout
# - Commits ALL to target branch
# - NO worktrees created

Do NOT cd anywhere. Stay in the project root checkout root.

Worktrees created later: After tasks are generated, use spec-kitty implement WP## to create workspace for each WP.

In repos with multiple features, always pass --feature <slug> to every spec-kitty command.

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Context Resolution (0.11.0+)

Before proceeding, resolve canonical command context:

spec-kitty agent context resolve --action tasks --json

Treat the resolver JSON as canonical for:

  • feature_slug
  • feature_dir
  • current_branch
  • target_branch
  • planning_base_branch
  • merge_target_branch
  • branch_matches_target
  • exact follow-up commands (check_prerequisites, finalize_tasks)

Prompts do not rediscover feature context. Commands do.

Outline

  1. Setup: Run the exact check_prerequisites command returned by the resolver and capture: If branch_matches_target is false, stop and tell the user the checkout is on the wrong planning branch instead of probing git manually in the prompt. CRITICAL: The command returns JSON with feature_dir as an ABSOLUTE path. It also returns runtime_vars.now_utc_iso (NOW_UTC_ISO) for deterministic timestamp fields. YOU MUST USE THIS PATH for ALL subsequent file operations. Example: feature_dir = "/path/to/project/kitty-specs/001-a-simple-hello" tasks.md location: feature_dir + "/tasks.md" prompt location: feature_dir + "/tasks/WP01-slug.md" DO NOT CREATE paths like:

- feature_dir - artifact_files / artifact_dirs (if present) - available_docs - current_branch - target_branch / base_branch - planning_base_branch / merge_target_branch - branch_matches_target All paths must be absolute. - ❌ tasks/WP01-slug.md (missing feature_dir prefix) - ❌ /tasks/WP01-slug.md (wrong root) - ❌ feature_dir/tasks/planned/WP01-slug.md (WRONG - no subdirectories!) - ❌ WP01-slug.md (wrong directory)

  1. Load design documents from feature_dir (only those present):

- Required: plan.md (tech architecture, stack), spec.md (user stories & priorities) - Optional: data-model.md (entities), contracts/ (API schemas), research.md (decisions), quickstart.md (validation scenarios) - Scale your effort to the feature: simple UI tweaks deserve lighter coverage, multi-system releases require deeper decomposition.

  1. Derive fine-grained subtasks (IDs T001, T002,...):

- Parse plan/spec to enumerate concrete implementation steps, tests (only if explicitly requested), migrations, and operational work. - Capture prerequisites, dependencies, and parallelizability markers ([P] means safe to parallelize per file/concern). - Maintain the subtask list internally; it feeds the work-package roll-up and the prompts.

  1. Roll subtasks into work packages (IDs WP01, WP02,...): IDEAL WORK PACKAGE SIZE (most important guideline): WHY SIZE MATTERS: NUMBER OF WPs: Let the work dictate the count GROUPING PRINCIPLES:

- Target: 3-7 subtasks per WP (results in 200-500 line prompts) - Maximum: 10 subtasks per WP (results in ~700 line prompts) - If more than 10 subtasks needed: Create additional WPs, don't pack them in - Too large (>10 subtasks, >700 lines): Agents get overwhelmed, skip details, make mistakes - Too small (<3 subtasks, <150 lines): Overhead of worktree creation not worth it - Just right (3-7 subtasks, 200-500 lines): Agent can hold entire context, implements thoroughly - Simple feature (5-10 subtasks total): 2-3 WPs - Medium feature (20-40 subtasks): 5-8 WPs - Complex feature (50+ subtasks): 10-20 WPs ← This is OK! - Better to have 20 focused WPs than 5 overwhelming WPs - Each WP should be independently implementable - Root in a single user story or cohesive subsystem - Ensure every subtask appears in exactly one work package - Name with succinct goal (e.g., "User Story 1 – Real-time chat happy path") - Record metadata: priority, success criteria, risks, dependencies, included subtasks

  1. Write tasks.md following the tasks template structure defined below in this prompt (do NOT write instructions to read a template file from .kittify/):

- Location: Write to feature_dir/tasks.md (use the absolute feature_dir path from step 1) - Populate the Work Package sections (setup, foundational, per-story, polish) with the WPxx entries - Under each work package include: - Summary (goal, priority, independent test) - Included subtasks (checkbox list referencing Txxx) - Implementation sketch (high-level sequence) - Parallel opportunities, dependencies, and risks - Preserve the checklist style so implementers can mark progress

  1. Generate prompt files (one per work package): IMPORTANT: All WP files live in flat tasks/ directory. OWNERSHIP METADATA (required by finalize-tasks): Each WP MUST declare these fields in frontmatter. If omitted, the finalizer infers them (often incorrectly, causing validation failures): Ownership rules:

- CRITICAL PATH RULE: All work package files MUST be created in a FLAT feature_dir/tasks/ directory, NOT in subdirectories! - Correct structure: feature_dir/tasks/WPxx-slug.md (flat, no subdirectories) - WRONG (do not create): feature_dir/tasks/planned/, feature_dir/tasks/doing/, or ANY lane subdirectories - WRONG (do not create): /tasks/, tasks/, or any path not under feature_dir - Use artifact_dirs.tasks_dir when available. - Do not shell out with mkdir -p; create-feature already creates tasks/ in normal flow. - If tasks/ is missing unexpectedly, report the mismatch instead of improvising shell directory setup. - For each work package: - Derive a kebab-case slug from the title; filename: WPxx-slug.md - Full path example: feature_dir/tasks/WP01-create-html-page.md (use ABSOLUTE path from feature_dir variable) - Follow the WP prompt template structure defined below in this prompt (do NOT write instructions to read a template file from .kittify/) to capture: - Frontmatter with work_package_id, subtasks array, lane: "planned", dependencies, planning_base_branch, merge_target_branch, branch_strategy, owned_files, authoritative_surface, execution_mode, and history entry - Objective, context, detailed guidance per subtask - A Branch Strategy section that repeats the planning branch, final merge target, and notes that the actual base_branch may later differ for stacked WPs during /spec-kitty.implement - Test strategy (only if requested) - Definition of Done, risks, reviewer guidance - Update tasks.md to reference the prompt filename - TARGET PROMPT SIZE: 200-500 lines per WP (results from 3-7 subtasks) - MAXIMUM PROMPT SIZE: 700 lines per WP (10 subtasks max) - If prompts are >700 lines: Split the WP - it's too large - execution_mode: Either "code_change" (source code) or "planning_artifact" (kitty-specs docs) - owned_files: List of glob patterns for files this WP touches. Example: ["src/myapp/auth/**", "tests/myapp/test_auth.py"] - authoritative_surface: Path prefix that must be a prefix of at least one owned_files entry. Example: "src/myapp/auth/" - No two WPs may have overlapping owned_files. - Use specific paths, not broad globs like src/**. - Agents working on a WP must not modify files outside their owned_files list. - Run spec-kitty agent feature finalize-tasks --validate-only --json to check ownership before committing.

  1. Finalize tasks with dependency parsing and commit: After generating all WP prompt files, run the finalization command to: CRITICAL: Run this command from repo root: spec-kitty agent feature finalize-tasks --json --feature <feature-slug> This step is MANDATORY for workspace-per-WP features. Without it: IMPORTANT - DO NOT COMMIT AGAIN AFTER THIS COMMAND:

- Parse dependencies from tasks.md - Update WP frontmatter with dependencies field - Validate dependencies (check for cycles, invalid references) - Commit all tasks to target branch - Dependencies won't be in frontmatter - Branching-strategy metadata won't be normalized into every WP prompt - Requirement refs won't be validated/normalized - Agents won't know which --base flag to use - Tasks won't be committed to target branch - finalize-tasks COMMITS the files automatically - JSON output includes "commit_created": true/false and "commit_hash" - If commit_created=true, files are ALREADY committed - do not run git commit again - Other dirty files shown by 'git status' (templates, config) are UNRELATED - Verify using the commit_hash from JSON output, not by running git add/commit again

  1. Report: Provide a concise outcome summary:

- Path to tasks.md - Work package count and per-package subtask tallies - Average prompt size (estimate lines per WP) - Validation: Flag if any WP has >10 subtasks or >700 estimated lines - Parallelization highlights - MVP scope recommendation (usually Work Package 1) - Prompt generation stats (files written, directory structure, any skipped items with rationale) - Finalization status (dependencies parsed, X WP files updated, committed to target branch) - Next suggested command (e.g., /spec-kitty.analyze or /spec-kitty.implement)

Context for work-package planning: $ARGUMENTS

The combination of tasks.md and the bundled prompt files must enable a new engineer to pick up any work package and deliver it end-to-end without further specification spelunking.

Dependency Detection (0.11.0+)

Parse dependencies from tasks.md structure:

The LLM should analyze tasks.md for dependency relationships:

  • Explicit phrases: "Depends on WP##", "Dependencies: WP##"
  • Phase grouping: Phase 2 WPs typically depend on Phase 1
  • Default to empty if unclear

Generate dependencies in WP frontmatter:

Each WP prompt file MUST include a dependencies field:

---
work_package_id: "WP02"
title: "Build API"
lane: "planned"
dependencies: ["WP01"]  # Generated from tasks.md
subtasks: ["T001", "T002"]
---

Include the correct implementation command:

  • No dependencies: spec-kitty implement WP01
  • With dependencies: spec-kitty implement WP02 --base WP01

The WP prompt must show the correct command so agents don't branch from the wrong base.

Requirement Reference Mapping (MANDATORY)

After creating all WP sections and prompt files, register requirement mappings using the CLI. The CLI validates each ref against spec.md and writes requirement_refs directly into each WP file's YAML frontmatter — no sidecar files needed.

Batch mode (recommended) — register all WP mappings at once:

spec-kitty agent tasks map-requirements --batch '{"WP01":["FR-001","FR-002"],"WP02":["FR-003","FR-004"]}' --json

Individual mode — register one WP at a time:

spec-kitty agent tasks map-requirements --wp WP01 --refs FR-001,FR-002 --json

The response includes a coverage summary showing which FRs are still unmapped. Keep calling until unmapped_functional is empty. Default mode unions new refs with existing ones in frontmatter. Use --replace to overwrite a WP's refs (e.g., to correct a bad mapping).

Work Package Sizing Guidelines (CRITICAL)

Ideal WP Size

Target: 3-7 subtasks per WP

  • Results in 200-500 line prompt files
  • Agent can hold entire context in working memory
  • Clear scope - easy to review
  • Parallelizable - multiple agents can work simultaneously

Examples of well-sized WPs:

  • WP01: Foundation Setup (5 subtasks, ~300 lines)

- T001: Create database schema - T002: Set up migration system - T003: Create base models - T004: Add validation layer - T005: Write foundation tests

  • WP02: User Authentication (6 subtasks, ~400 lines)

- T006: Implement login endpoint - T007: Implement logout endpoint - T008: Add session management - T009: Add password reset flow - T010: Write auth tests - T011: Add rate limiting

Maximum WP Size

Hard limit: 10 subtasks, ~700 lines

  • Beyond this, agents start making mistakes
  • Prompts become overwhelming
  • Reviews take too long
  • Integration risk increases

If you need more than 10 subtasks: SPLIT into multiple WPs.

Number of WPs: No Arbitrary Limit

DO NOT limit based on WP count. Limit based on SIZE.

  • 20 WPs of 5 subtasks each = 100 subtasks, manageable prompts
  • 5 WPs of 20 subtasks each = 100 subtasks, overwhelming 1400-line prompts

Feature complexity scales with subtask count, not WP count:

  • Simple feature: 10-15 subtasks → 2-4 WPs
  • Medium feature: 30-50 subtasks → 6-10 WPs
  • Complex feature: 80-120 subtasks → 15-20 WPs ← Totally fine!
  • Very complex: 150+ subtasks → 25-30 WPs ← Also fine!

The goal is manageable WP size, not minimizing WP count.

When to Split a WP

Split if ANY of these are true:

  • More than 10 subtasks
  • Prompt would exceed 700 lines
  • Multiple independent concerns mixed together
  • Different phases or priorities mixed
  • Agent would need to switch contexts multiple times

How to split:

  • By phase: Foundation WP01, Implementation WP02, Testing WP03
  • By component: Database WP01, API WP02, UI WP03
  • By user story: Story 1 WP01, Story 2 WP02, Story 3 WP03
  • By type of work: Code WP01, Tests WP02, Migration WP03, Docs WP04

When to Merge WPs

Merge if ALL of these are true:

  • Each WP has <3 subtasks
  • Combined would be <7 subtasks
  • Both address the same concern/component
  • No natural parallelization opportunity
  • Implementation is highly coupled

Don't merge just to hit a WP count target!

Task Generation Rules

Tests remain optional. Only include testing tasks/steps if the feature spec or user explicitly demands them.

  1. Subtask derivation:

- Assign IDs Txxx sequentially in execution order. - Use [P] for parallel-safe items (different files/components). - Include migrations, data seeding, observability, and operational chores. - Ideal subtask granularity: One clear action (e.g., "Create user model", "Add login endpoint") - Too granular: "Add import statement", "Fix typo" (bundle these) - Too coarse: "Build entire API" (split into endpoints)

  1. Work package grouping:

- Focus on SIZE first, count second - Target 3-7 subtasks per WP (200-500 line prompts) - Maximum 10 subtasks per WP (700 line prompts) - Keep each work package laser-focused on a single goal - Avoid mixing unrelated concerns - Let complexity dictate WP count: 20+ WPs is fine for complex features

  1. Prioritisation & dependencies:

- Sequence work packages: setup → foundational → story phases (priority order) → polish. - Call out inter-package dependencies explicitly in both tasks.md and the prompts. - Front-load infrastructure/foundation WPs (enable parallelization)

  1. Prompt composition:

- Mirror subtask order inside the prompt. - Provide actionable implementation and test guidance per subtask—short for trivial work, exhaustive for complex flows. - Aim for 30-70 lines per subtask in the prompt (includes purpose, steps, files, validation) - Surface risks, integration points, and acceptance gates clearly so reviewers know what to verify. - Include examples where helpful (API request/response shapes, config file structures, test cases)

  1. Quality checkpoints:

- After drafting WPs, review each prompt size estimate - If any WP >700 lines: STOP and split it - If most WPs <200 lines: Consider merging related ones - Aim for consistency: Most WPs should be similar size (within 200-line range) - Think like an implementer: Can I complete this WP in one focused session? If not, it's too big.

  1. Think like a reviewer: Any vague requirement should be tightened until a reviewer can objectively mark it done or not done.

Step-by-Step Process

Step 1: Detect Feature Context

Resolve the feature slug from explicit user direction, current branch, or current directory path.

If ambiguous, run check-prerequisites once without --feature, parse the JSON candidate list, and select one explicit feature slug.

Step 2: Setup

Run spec-kitty agent feature check-prerequisites --json --paths-only --include-tasks --feature <feature-slug> and capture feature_dir.

Step 3: Load Design Documents

Read from feature_dir:

  • spec.md (required)
  • plan.md (required)
  • data-model.md (optional)
  • research.md (optional)
  • contracts/ (optional)

Step 4: Derive ALL Subtasks

Create complete list of subtasks with IDs T001, T002, etc.

Don't worry about count yet - capture EVERYTHING needed.

Step 5: Group into Work Packages

SIZING ALGORITHM:

For each cohesive unit of work:
  1. List related subtasks
  2. Count subtasks
  3. Estimate prompt lines (subtasks × 50 lines avg)

  If subtasks <= 7 AND estimated lines <= 500:
    ✓ Good WP size - create it

  Else if subtasks > 10 OR estimated lines > 700:
    ✗ Too large - split into 2+ WPs

  Else if subtasks < 3 AND can merge with related WP:
    → Consider merging (but don't force it)

Examples:

Good sizing:

  • WP01: Database Foundation (5 subtasks, ~300 lines) ✓
  • WP02: User Authentication (7 subtasks, ~450 lines) ✓
  • WP03: Admin Dashboard (6 subtasks, ~400 lines) ✓

Too large - MUST SPLIT:

  • ❌ WP01: Entire Backend (25 subtasks, ~1500 lines)

- ✓ Split into: DB Layer (5), Business Logic (6), API Layer (7), Auth (7)

Too small - CONSIDER MERGING:

  • WP01: Add config file (2 subtasks, ~100 lines)
  • WP02: Add logging (2 subtasks, ~120 lines)

- ✓ Merge into: WP01: Infrastructure Setup (4 subtasks, ~220 lines)

Step 6: Write tasks.md

Create work package sections with:

  • Summary (goal, priority, test criteria)
  • Included subtasks (checkbox list)
  • Implementation notes
  • Parallel opportunities
  • Dependencies
  • Estimated prompt size (e.g., "~400 lines")

Step 7: Generate WP Prompt Files

For each WP, generate feature_dir/tasks/WPxx-slug.md using the template.

CRITICAL VALIDATION: After generating each prompt:

  1. Count lines in the prompt
  2. If >700 lines: GO BACK and split the WP
  3. If >1000 lines: STOP - this will fail - you MUST split it

Self-check:

  • Subtask count: 3-7? ✓ | 8-10? ⚠️ | 11+? ❌ SPLIT
  • Estimated lines: 200-500? ✓ | 500-700? ⚠️ | 700+? ❌ SPLIT
  • Can implement in one session? ✓ | Multiple sessions needed? ❌ SPLIT

Step 8: Finalize Tasks

Run the resolver-returned finalize_tasks command to:

  • Parse dependencies
  • Update frontmatter
  • Validate (cycles, invalid refs)
  • Commit to target branch

DO NOT run git commit after this - finalize-tasks commits automatically. Check JSON output for "commit_created": true and "commit_hash" to verify.

Step 9: Report

Provide summary with:

  • WP count and subtask tallies
  • Size distribution (e.g., "6 WPs ranging from 250-480 lines")
  • Size validation (e.g., "✓ All WPs within ideal range" OR "⚠️ WP05 is 820 lines - consider splitting")
  • Parallelization opportunities
  • MVP scope
  • Next command

⚠️ Common Mistakes to Avoid

❌ MISTAKE 1: Optimizing for WP Count

Bad thinking: "I'll create exactly 5-7 WPs to keep it manageable" → Results in: 20 subtasks per WP, 1200-line prompts, overwhelmed agents

Good thinking: "Each WP should be 3-7 subtasks (200-500 lines). If that means 15 WPs, that's fine." → Results in: Focused WPs, successful implementation, happy agents

❌ MISTAKE 2: Token Conservation During Planning

Bad thinking: "I'll save tokens by writing brief prompts with minimal guidance" → Results in: Agents confused during implementation, asking clarifying questions, doing work wrong, requiring rework

Good thinking: "I'll invest tokens now to write thorough prompts with examples and edge cases" → Results in: Agents implement correctly the first time, no rework needed, net token savings

❌ MISTAKE 3: Mixing Unrelated Concerns

Bad example: WP03: Misc Backend Work (12 subtasks)

  • T010: Add user model
  • T011: Configure logging
  • T012: Set up email service
  • T013: Add admin dashboard
  • ... (8 more unrelated tasks)

Good approach: Split by concern

  • WP03: User Management (T010-T013, 4 subtasks)
  • WP04: Infrastructure Services (T014-T017, 4 subtasks)
  • WP05: Admin Dashboard (T018-T021, 4 subtasks)

❌ MISTAKE 4: Insufficient Prompt Detail

Bad prompt (~20 lines per subtask):

### Subtask T001: Add user authentication

**Purpose**: Implement login

**Steps**:
1. Create endpoint
2. Add validation
3. Test it

Good prompt (~60 lines per subtask):

### Subtask T001: Implement User Login Endpoint

**Purpose**: Create POST /api/auth/login endpoint that validates credentials and returns JWT token.

**Steps**:
1. Create endpoint handler in `src/api/auth.py`:
   - Route: POST /api/auth/login
   - Request body: `{email: string, password: string}`
   - Response: `{token: string, user: UserProfile}` on success
   - Error codes: 400 (invalid input), 401 (bad credentials), 429 (rate limited)

2. Implement credential validation:
   - Hash password with bcrypt (matches registration hash)
   - Compare against stored hash from database
   - Use constant-time comparison to prevent timing attacks

3. Generate JWT token on success:
   - Include: user_id, email, issued_at, expires_at (24 hours)
   - Sign with SECRET_KEY from environment
   - Algorithm: HS256

4. Add rate limiting:
   - Max 5 attempts per IP per 15 minutes
   - Return 429 with Retry-After header

**Files**:
- `src/api/auth.py` (new file, ~80 lines)
- `tests/api/test_auth.py` (new file, ~120 lines)

**Validation**:
- [ ] Valid credentials return 200 with token
- [ ] Invalid credentials return 401
- [ ] Missing fields return 400
- [ ] Rate limit enforced (test with 6 requests)
- [ ] JWT token is valid and contains correct claims
- [ ] Token expires after 24 hours

**Edge Cases**:
- Account doesn't exist: Return 401 (same as wrong password - don't leak info)
- Empty password: Return 400
- SQL injection in email field: Prevented by parameterized queries
- Concurrent login attempts: Handle with database locking

Remember

This is the most important planning work you'll do.

A well-crafted set of work packages with detailed prompts makes implementation smooth and parallelizable.

A rushed job with vague, oversized WPs causes:

  • Agents getting stuck
  • Implementation taking 2-3x longer
  • Rework and review cycles
  • Feature failure

Invest the tokens now. Be thorough. Future agents will thank you.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.07%
按下载量换算65

Claude

31.89%
按下载量换算58

Cursor

18.83%
按下载量换算34

Gemini CLI

8.62%
按下载量换算16

安全审计

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通过

Socket

通过

Snyk

通过

权限和风险

执行命令

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