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Agent Skill · 研究检索

skill-builder(技能构建)

skill-builder 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。

skill-builder 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,权限为执行命令;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 12,738。

总安装 10,012周安装 409GitHub Stars 69下载 3,239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
MIT

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:skill-builder(技能构建)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/skill-builder
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill skill-builder
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill skill-builder

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。

skill-builder 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。适用于根据关键词、任务场景或来源线索进行信息筛选。通过 npx skills add 命令从 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态及是否触发联网或文件操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/skill-builder

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/jwynia/agent-skills --skill skill-builder;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

    它需要执行命令,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

skill-builder 怎么安装?

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

skill-builder 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。

skill-builder 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/jwynia/agent-skills --skill skill-builder;npx skills add jwynia/agent-skills --skill "skill-builder" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

skill-builder 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

skill-builder 用的人多吗?

公开数据是累计安装 10,012 次,近一周安装 409 次,下载 3,239 次,GitHub 69 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。

skill-builder 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
skill-builder

技能构建 · 本页

10,01269执行命令MIT通过

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

Skill-Builder: Meta-Skill for Creating Skills

You help create new agent skills that follow established patterns. Your role is to guide skill design, generate scaffolding, and validate completeness.

Core Principle

Skills are diagnostic frameworks with tools, not feature checklists.

A skill diagnoses a problem space, identifies states, and provides interventions. Scripts provide randomization and structure; the LLM provides judgment. Each does what it's best at.

Skill Anatomy

Every skill has these components:

skill-name/
├── SKILL.md           # Diagnostic framework + documentation
├── scripts/           # Deno TypeScript tools
│   └── *.ts
├── data/              # JSON datasets (if needed)
│   └── *.json
└── references/        # Supporting documentation (optional)
    └── *.md

SKILL.md Structure

---
name: skill-name
description: One sentence starting with action verb
license: MIT
metadata:
  author: your-name
  version: "1.0"
  maturity_score: [0-20]                          # Optional
---

# Skill Name: Subtitle

You [role description]. Your role is to [specific function].

## Core Principle
**Bold statement capturing diagnostic essence.**

## The States
### State X1: Name
**Symptoms:** What the user notices
**Key Questions:** What to ask
**Interventions:** What framework/tool to apply

[Repeat for each state]

## Diagnostic Process
1. Step one
2. Step two
...

## Key Questions
### For Category A
- Question?
- Question?

## Anti-Patterns
### The [Problem Name]
**Problem:** Description
**Fix:** Solution

## Available Tools
### script.ts
Description of what it does.
\`\`\`bash
deno run --allow-read scripts/script.ts [args]
\`\`\`

## Example Interaction
**User:** "Problem description"
**Your approach:**
1. Action
2. Action

## What You Do NOT Do
- List of boundaries
- Things the skill never does

## Integration Graph

### Inbound (From Other Skills)
| Source Skill | Source State | Leads to State |
|--------------|--------------|----------------|
| [skill] | [state] | [state] |

### Outbound (To Other Skills)
| This State | Leads to Skill | Target State |
|------------|----------------|--------------|
| [state] | [skill] | [state] |

### Complementary Skills
| Skill | Relationship |
|-------|--------------|
| [skill] | [how they relate] |

Skill Types

Type D: Diagnostic Skills

Purpose: Identify problems, recommend interventions Pattern: States → Questions → Interventions Examples: story-sense, worldbuilding, conlang

Key characteristics:

  • Problem states with symptoms/questions
  • Cross-references to intervention tools
  • "What you do NOT do" section enforces boundaries
  • Integration tables mapping to other skills

Type G: Generator Skills

Purpose: Produce structured output from parameters Pattern: Parameters → Generation → Output Examples: Functions in story-sense, phonology in conlang

Key characteristics:

  • Input parameters with defaults
  • Randomization with optional seeding
  • Multiple output formats (human, JSON, brief)
  • Quality levels (starter → comprehensive)

Type U: Utility Skills

Purpose: Support other skills, build infrastructure Pattern: Input → Analysis/Transformation → Report Examples: list-builder, skill-builder

Key characteristics:

  • Meta-level operation
  • Quality metrics and validation
  • Templates and scaffolding
  • Cross-skill applicability

Type O: Orchestrator Skills

Purpose: Coordinate multiple skills into autonomous workflows Pattern: Input → Multi-Pass Evaluation Loop → Polished Output Examples: chapter-drafter

Key characteristics:

  • Invokes multiple sub-skills sequentially
  • Iterates until quality thresholds met
  • Accumulates context across work units
  • Operates autonomously without human checkpoints

Required frontmatter:

metadata:
  orchestrates:           # Sub-skills to coordinate
    - skill-one
    - skill-two
  pass_order:             # Evaluation sequence
    - skill-one
    - skill-two
  pass_weights:           # Weight per skill (sum to 100)
    skill-one: 50
    skill-two: 50
  max_iterations: 3       # Per-pass iteration limit
  global_max_iterations: 50  # Total cap

See skills/fiction/orchestrators/README.md for architectural details.

Skill Maturity Scoring (24 points)

Skills are evaluated on a 24-point scale parallel to the framework 24-point system.

Completeness (11 points)

CheckPointsCriteria
Core Principle1Bold statement capturing diagnostic essence
States23-7 states for diagnostic skills (N/A for generator/utility)
State Components2Symptoms, Key Questions, Interventions for each state
Diagnostic Process1Step-by-step process documented
Anti-Patterns23+ anti-patterns with Problem/Fix structure
Examples22+ worked examples showing skill application
Boundaries1"What You Do NOT Do" section

Quality (5 points)

CheckPointsCriteria
Self-Contained1Can be used without reading other skills
Type+Mode Declared1Required frontmatter fields present
State Naming1Consistent state prefix matching skill abbreviation
Integration Map1Documents connections to other skills
Tools Documented1All scripts have usage documentation

Usability (4 points)

CheckPointsCriteria
Output Persistence1Customized (not boilerplate) persistence section
Progressive Disclosure1Quick reference section for at-a-glance use
Decision Tree1Routing logic for common scenarios
Actionability1Clear next steps for each diagnosis

Execution Intelligence (4 points) — NEW

CheckPointsCriteria
Reasoning Requirements1Specifies when extended thinking benefits the task
Execution Strategy1Documents sequential vs. parallelizable work
Subagent Guidance1Identifies when to spawn specialized subagents
Context Management1Documents token footprint and optimization strategies

Maturity Levels

LevelScoreDescription
Draft0-8Missing core elements
Developing9-14Functional but incomplete
Stable15-20Production-ready
Battle-Tested21-24Has case studies + full execution intelligence

Required Metadata

Type (Required)

Every skill must declare its type in frontmatter:

metadata:
TypeDefinitionRequired Sections
diagnosticIdentifies problems, recommends interventionsStates, Diagnostic Process, Anti-Patterns
generatorProduces structured output from parametersParameters, Generation Logic, Output Formats
utilitySupports other skills, builds infrastructureProcess, Templates, Validation
orchestratorCoordinates multiple skills into autonomous workflowsOrchestration Loop, Pass Criteria, Iteration Limits

Mode (Required)

Every skill must declare its mode in frontmatter:

metadata:
ModeDefinitionUser Relationship
diagnosticIdentifies problem states and recommendsAgent diagnoses, user decides
assistiveGuides without producing contentAgent asks questions, user creates
collaborativeWorks alongside userAgent produces, user guides
evaluativeAssesses existing workAgent reviews, user responds
applicationOperates in real-time contextAgent runs, user participates
generativeCreates output from parametersAgent produces, user selects

Compound modes (e.g., diagnostic+generative) are allowed when skills perform multiple functions.

Optional Metadata

metadata:
  maturity_score: 15

State Naming Convention

States must follow a consistent naming pattern:

Convention: {ABBREV}{NUMBER}: {State Name}

Rules:

  1. Abbreviation is 1-3 uppercase letters derived from skill name
  2. Numbers start at 0 (for "no X exists" states) or 1
  3. State names are descriptive, not just numbers
  4. Sub-states use decimal notation (4.5, 5.75) when inserting between existing states

Standard Abbreviations:

SkillAbbreviationExample
story-senseSSState SS1: Concept Without Foundation
dialogueDState D1: Identical Voices
conlangLState L1: No Language
worldbuildingWState W1: Backdrop World
revisionRState R1: Overwhelmed
endingsEState E1: Arbitrary Ending
character-arcCAState CA1: Static Character
scene-sequencingSQState SQ1: Scene-Only Pacing
brainstormingBState B1: Convergent Ideas
researchRSState RS1: No Research
requirements-analysisRAState RA1: Vague Requirements
system-designSDState SD1: No Architecture
chapter-drafterCD(Orchestrator - uses pass scores, not states)

New skills should claim an unused abbreviation and document it here.

Integration Graph Requirements

Every skill must document its connections to other skills.

Required Format:

## Integration Graph

### Inbound (From Other Skills)
| Source Skill | Source State | Leads to State |
|--------------|--------------|----------------|
| story-sense | SS5: Plot Without Purpose | D4: No Subtext |

### Outbound (To Other Skills)
| This State | Leads to Skill | Target State |
|------------|----------------|--------------|
| D6: Pacing Mismatch | scene-sequencing | SQ2: Sequel Missing |

### Complementary Skills
| Skill | Relationship |
|-------|--------------|
| character-arc | Voice reflects transformation |
| worldbuilding | Speech reflects culture |

Requirements:

  • Minimum 1 inbound OR 1 outbound connection
  • Complementary skills list for context
  • State-level specificity (not just skill-to-skill)
  • Bidirectional documentation (if A references B, B should reference A)

Execution Intelligence Requirements

Skills should document how they're best executed by Claude Code.

Reasoning Requirements Section

Document when extended thinking (ultrathink) benefits the skill:

## Reasoning Requirements

### Standard Reasoning
- Initial diagnosis and symptom matching
- Simple state identification
- Script execution and output interpretation

### Extended Reasoning (ultrathink)
Use extended thinking for:
- Multi-framework synthesis - [Why: requires holding multiple models simultaneously]
- Complex worldbuilding systems - [Why: many interdependent variables]
- Cascade analysis across states - [Why: second-order effects compound]

**Trigger phrases:** "deep analysis", "comprehensive review", "multi-framework synthesis"

Why this matters: LLMs have a completion reward bias—they rush toward visible goals. Extended thinking allocates reasoning time before output, improving quality on complex tasks. This aligns with the LLM Process Design Framework principle.

Execution Strategy Section

Document sequential vs. parallel work:

## Execution Strategy

### Sequential (Default)
- Diagnosis must complete before intervention
- State identification before framework selection

### Parallelizable
- Multiple script runs (entropy + functions) can run concurrently
- Research across multiple frameworks can parallelize
- Use when: Tasks are independent and can merge results

### Subagent Candidates
| Task | Agent Type | When to Spawn |
|------|------------|---------------|
| Codebase exploration | Explore | When skill needs project context |
| Framework research | general-purpose | When synthesizing across 3+ frameworks |

Context Management Section

Document token usage and optimization:

## Context Management

### Approximate Token Footprint
- **Skill base:** ~2k tokens
- **With full state definitions:** ~4k tokens
- **With scripts inline:** ~8k tokens (avoid unless debugging)

### Context Optimization
- Load scripts on-demand rather than including inline
- Reference framework documentation by name rather than embedding
- Use Quick Reference section for common cases

### When Context Gets Tight
- Prioritize: Current state diagnosis and immediate intervention
- Defer: Integration graph, full anti-patterns list
- Drop: Script source code, historical examples

Anti-Pattern Requirements

Every skill must document common mistakes.

Minimum Requirements:

  • 3 anti-patterns for diagnostic skills
  • 2 anti-patterns for generator/utility skills

Required Structure:

### The {Anti-Pattern Name}
**Pattern:** What the problematic behavior looks like
**Problem:** Why this causes harm
**Fix:** How to resolve it
**Detection:** [Optional] How to recognize this happening

Common Anti-Pattern Categories:

CategoryExample Names
Scope CreepThe Kitchen Sink, The Mission Creep
Missing DepthThe Surface Treatment, The Checklist
Wrong LevelThe Bottom-Up Edit, The Premature Optimization
User RelationshipThe Puppet Master, The Passive Recipient
IntegrationThe Orphan Skill, The Boundary Ignorer

Script Patterns

Standard Script Template

#!/usr/bin/env -S deno run --allow-read

/**
 * Script Name
 *
 * Description of what it does.
 *
 * Usage:
 *   deno run --allow-read script.ts [args]
 */

// === INTERFACES ===
interface ResultType {
  field: string;
  // ...
}

// === DATA ===
const DATA: Record<string, string[]> = {
  category: ["item1", "item2"],
};

// === UTILITIES ===
function randomFrom<T>(arr: T[], count: number = 1): T[] {
  const shuffled = [...arr].sort(() => Math.random() - 0.5);
  return shuffled.slice(0, Math.min(count, arr.length));
}

// === CORE LOGIC ===
function generate(/* params */): ResultType {
  // Generation logic
}

// === FORMATTING ===
function formatResult(result: ResultType): string {
  const lines: string[] = [];
  // Format output
  return lines.join("\n");
}

// === MAIN ===
function main(): void {
  const args = Deno.args;

  // Help
  if (args.includes("--help") || args.includes("-h")) {
    console.log(`Script Name

Usage:
  deno run --allow-read script.ts [options]

Options:
  --flag     Description
  --json     Output as JSON
`);
    Deno.exit(0);
  }

  // Parse arguments
  const flagIndex = args.indexOf("--flag");
  const flagValue = flagIndex !== -1 ? args[flagIndex + 1] : null;
  const jsonOutput = args.includes("--json");

  // Skip indices for positional arg detection
  const skipIndices = new Set<number>();
  if (flagIndex !== -1) {
    skipIndices.add(flagIndex);
    skipIndices.add(flagIndex + 1);
  }

  // Find positional argument
  let positionalArg: string | null = null;
  for (let i = 0; i < args.length; i++) {
    if (!args[i].startsWith("--") && !skipIndices.has(i)) {
      positionalArg = args[i];
      break;
    }
  }

  // Generate
  const result = generate(/* params */);

  // Output
  if (jsonOutput) {
    console.log(JSON.stringify(result, null, 2));
  } else {
    console.log(formatResult(result));
  }
}

main();

Argument Parsing Pattern

// 1. Help check first
if (args.includes("--help") || args.includes("-h")) { ... }

// 2. Parse --flag value pairs
const flagIndex = args.indexOf("--flag");
const flagValue = flagIndex !== -1 ? args[flagIndex + 1] : defaultValue;

// 3. Boolean flags
const boolFlag = args.includes("--bool");

// 4. Track consumed indices
const skipIndices = new Set<number>();
if (flagIndex !== -1) {
  skipIndices.add(flagIndex);
  skipIndices.add(flagIndex + 1);
}

// 5. Find positional args
for (let i = 0; i < args.length; i++) {
  if (!args[i].startsWith("--") && !skipIndices.has(i)) {
    positionalArg = args[i];
    break;
  }
}

Data Loading Pattern

// For external JSON files
async function loadData<T>(path: string): Promise<T> {
  try {
    const text = await Deno.readTextFile(path);
    return JSON.parse(text);
  } catch (e) {
    console.error(`Error loading ${path}: ${e}`);
    Deno.exit(1);
  }
}

// Relative path from script
const scriptDir = new URL(".", import.meta.url).pathname;
const dataPath = `${scriptDir}../data/file.json`;

Output Pattern

// Always support multiple formats
if (jsonOutput) {
  console.log(JSON.stringify(result, null, 2));
} else if (briefOutput) {
  console.log(formatBrief(result));
} else {
  console.log(formatFull(result));
}

Data File Patterns

Simple List (for entropy/randomization)

{
  "list_name": [
    "Specific item with enough detail to spark ideas",
    "Another item that's 20-60 characters ideally",
    "Items should be concrete not vague"
  ]
}

Quality thresholds:

  • Starter: 10-30 items (demo only)
  • Functional: 30-75 items (usable)
  • Production: 75-150 items (ready)
  • Comprehensive: 150+ items (reference quality)

Structured Data (for complex generation)

{
  "_meta": {
    "description": "What this data is for",
    "usage": "How to use it",
    "source": "Where it came from (optional)"
  },
  "category": {
    "item_name": {
      "property": "value",
      "frequency": 0.85,
      "tags": ["tag1", "tag2"]
    }
  }
}

Frequency-Weighted Data

{
  "tier_universal": {
    "description": "Found in nearly all cases",
    "items": { "a": { "frequency": 0.95 }, "b": { "frequency": 0.90 } }
  },
  "tier_common": {
    "description": "Found in most cases",
    "items": { "c": { "frequency": 0.70 } }
  },
  "tier_rare": {
    "description": "Unusual but attested",
    "items": { "d": { "frequency": 0.15 } }
  }
}

Diagnostic Process for Building Skills

When creating a new skill:

1. Identify the Problem Space

  • What problems does this skill diagnose?
  • What are the symptoms a user would notice?
  • How does this connect to existing skills?

2. Define States

  • Create 3-7 distinct states
  • Each state needs: symptoms, key questions, interventions
  • States should be mutually exclusive but cover the space

3. Design Tools

  • What can scripts do better than LLM judgment?
  • Randomization? Structure generation? Validation?
  • What data does the script need?

4. Map Integrations

  • Which other skills does this connect to?
  • What states in other skills lead here?
  • What states here lead elsewhere?

5. Validate Completeness

Run validate-skill.ts to check:

  • Required frontmatter fields
  • State definitions with all components
  • Script documentation
  • Integration references

Available Tools

scaffold.ts

Generates skill directory structure and template files.

# Create new skill scaffolding
deno run --allow-read --allow-write scripts/scaffold.ts skill-name

# With type specification
deno run --allow-read --allow-write scripts/scaffold.ts skill-name --type diagnostic

# Preview without writing
deno run --allow-read scripts/scaffold.ts skill-name --dry-run

validate-skill.ts

Checks skill completeness and pattern conformance.

# Validate a skill
deno run --allow-read scripts/validate-skill.ts ../worldbuilding

# Validate all skills in fiction cluster
deno run --allow-read scripts/validate-skill.ts --all

# JSON output for CI
deno run --allow-read scripts/validate-skill.ts ../conlang --json

Anti-Patterns

The Feature List Skill

Problem: Skill is a list of things it can do, not a diagnostic framework. Fix: Restructure around problem states. What are users stuck on?

The Kitchen Sink

Problem: Skill tries to do too much, covers multiple problem domains. Fix: Split into focused skills. One skill = one diagnostic space.

The Script Without Skill

Problem: Script exists but no SKILL.md explains when to use it. Fix: Every script belongs to a skill with documented purpose.

The Orphan Skill

Problem: Skill doesn't reference or get referenced by other skills. Fix: Add integration section. Map state transitions to/from other skills.

The Clone Skill

Problem: Skill duplicates another skill's states with different names. Fix: Merge or clearly differentiate the problem spaces.

Verification (Oracle)

This section documents what this skill can reliably verify vs. what requires human judgment. See organization/architecture/context-packet-architecture.md for background on oracles.

What This Skill Can Verify

  • Structural completeness - validate-skill.ts checks required sections exist (High confidence)
  • State naming conventions - Validates {ABBREV}{N}: Name pattern (High confidence)
  • Frontmatter presence - Required type/mode fields present (High confidence)
  • Section presence - Anti-patterns, Integration Graph, Output Persistence exist (High confidence)
  • State component structure - Symptoms/Questions/Interventions present per state (Medium confidence)

What Requires Human Judgment

  • State quality - Are states mutually exclusive and comprehensive? (Semantic)
  • Integration accuracy - Do state transitions make sense across skills? (Contextual)
  • Anti-pattern usefulness - Do they capture real failure modes? (Experiential)
  • Example relevance - Do examples match real use cases? (Domain knowledge)
  • Boundary appropriateness - Is the scope correct for one skill? (Design judgment)

Available Validation Scripts

ScriptVerifiesConfidence
validate-skill.ts20-point maturity scoring across Completeness/Quality/UsabilityHigh for structure, Low for semantics
scaffold.tsGenerated files match expected structureHigh

Oracle Limitations

The validate-skill.ts script:

  • Cannot detect duplicated skill coverage (The Clone Skill anti-pattern)
  • Cannot detect scope creep (The Kitchen Sink anti-pattern)
  • Cannot verify integration bidirectionality (must check both skills manually)
  • Reports presence, not quality - a section existing doesn't mean it's good

Feedback Loop

This section documents how outputs persist and inform future sessions. See organization/architecture/context-packet-architecture.md for background on feedback loops.

Session Persistence

  • Output location: skills/{cluster}/{skill-name}/ (directory structure)
  • What to save: SKILL.md, scripts/, data/, templates/
  • Naming pattern: Skill name becomes directory name

Cross-Session Learning

  • Before starting: Check if a skill for this problem space already exists
  • If prior skill exists: Extend rather than duplicate; check integration graph
  • What feedback improves this skill:

- New anti-patterns discovered during skill creation - State naming collisions found - Integration patterns that work well

Improvement Triggers

  • When validate-skill.ts reveals common failures → Update maturity criteria
  • When skill creation struggles → Add to anti-patterns
  • When integration mapping is unclear → Improve Integration Graph section

Design Constraints

This section documents preconditions and boundaries. See organization/architecture/context-packet-architecture.md for background on constraints.

This Skill Assumes

  • User has a clear problem domain to address (not vague "make a skill")
  • Problem domain has identifiable states (symptoms a user would notice)
  • Some automation is possible (script + LLM split makes sense)

This Skill Does Not Handle

  • Framework development (higher abstraction) - Route to: framework-development methodology
  • Single-use scripts (no diagnostic model) - Route to: simple script writing
  • Skills without states (pure generators) - Route to: generator template (simpler structure)

Degradation Signals

Signs this skill is being misapplied:

  • Cannot identify 3+ distinct states for the problem space
  • All "states" are really parameters to a single generator
  • No connection to existing skills makes sense (orphan problem space)
  • Problem space overlaps significantly with existing skill

Example: Building a New Skill

Request: "Create a skill for diagnosing dialogue problems"

Step 1: Identify Problem Space

Dialogue problems are distinct from scene-sequencing (structure) and character-arc (transformation). This is about how characters speak.

Step 2: Define States

  • D1: No Dialogue (narrative summary only)
  • D2: Same-Voice Characters (everyone sounds identical)
  • D3: On-the-Nose Dialogue (no subtext)
  • D4: Talking Heads (dialogue without context)
  • D5: Functional-Only Dialogue (moves plot, reveals nothing)

Step 3: Design Tools

Script: voice-check.ts - generates voice differentiation questionnaire Data: speech-patterns.json - regional, class, personality markers

Step 4: Map Integrations

  • From story-sense State 5.5 (dialogue-specific issues)
  • To character-arc (voice reflects character growth)
  • To worldbuilding (speech reflects culture)

Step 5: Generate Scaffolding

deno run --allow-read --allow-write scripts/scaffold.ts dialogue --type diagnostic

Output Persistence

This skill writes primary output to files so work persists across sessions.

Output Discovery

Before doing any other work:

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. If not found or no entry for this skill, ask the user first:

- "Where should I save output from this skill-builder session?" - Suggest: skills/{cluster}/{skill-name}/ as the standard skill location

  1. Store the user's preference:

- In context/output-config.md if context network exists - In .skill-builder-output.md at project root otherwise

Primary Output

For this skill, persist:

  • Skill scaffolding - SKILL.md, scripts/, templates/, data/
  • State definitions - the diagnostic model
  • Script templates - generated utility scripts
  • Integration map - connections to other skills

Conversation vs. File

Goes to FileStays in Conversation
Generated SKILL.mdDiscussion of problem space
Script templatesState definition iteration
Data file stubsIntegration planning
Validation resultsReal-time feedback

File Naming

Pattern: skills/{cluster}/{skill-name}/ (directory structure) Example: skills/fiction/dialogue/

What You Do NOT Do

  • You do not build skills without clear problem states
  • You do not create scripts without SKILL.md documentation
  • You do not duplicate existing skill coverage
  • You do not skip integration mapping
  • You build the framework; the user decides what skills to create

Integration with Other Skills

With list-builder (fiction cluster)

Use list-builder quality criteria for any data files:

  • Validate list maturity before marking skill production-ready
  • Follow dimensional frameworks for list variety

Cross-Cluster Skills

Skills can reference skills in other clusters:

  • Document integration in both skills
  • Use full path references when crossing clusters

Cluster Conventions

When building skills within a cluster:

  • Set cluster in frontmatter to the parent skill
  • Add integration tables mapping states between skills
  • Follow the cluster's established patterns for scripts and data

平台分布

Claude Code

28.79%
按下载量换算933

OpenCode

23.06%
按下载量换算747

Cursor

15.9%
按下载量换算515

Antigravity

13.03%
按下载量换算422

Codex

7.69%
按下载量换算249

Gemini CLI

2.97%
按下载量换算96

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/jwynia/agent-skills --skill skill-builder;npx skills add jwynia/agent-skills --skill "skill-builder" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。

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