skillkit

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Section 1: Intent Detection & Routing

第1部分:意图检测与路由

Detect user intent, route to appropriate workflow.
IntentKeywordsRoute To
Full skill creation"create skill", "build skill", "new skill"Section 2
Subagent creation"create subagent", "build subagent", "new subagent"Section 6
Validation"validate", "check quality"Section 3
Decision"Skills vs Subagents", "decide", "which to use"Section 4
Migration"convert", "migrate doc"Section 5
Single tool"validate only", "estimate tokens", "scan"Section 7
PROCEED to corresponding section after intent detection.
Stop Condition (Mandatory):
  • If multiple routes match or intent is ambiguous: stop, ask user to choose one route.
  • Do not proceed until user confirms the route.
Workflow Value: Research-driven approach validates design before building. Sequential steps with checkpoints produce 9.0/10+ quality vs ad-hoc creation.

检测用户意图,路由至对应的工作流。
意图关键词路由至
完整Skill创建"create skill", "build skill", "new skill"第2部分
Subagent创建"create subagent", "build subagent", "new subagent"第6部分
验证"validate", "check quality"第3部分
决策"Skills vs Subagents", "decide", "which to use"第4部分
迁移"convert", "migrate doc"第5部分
单一工具"validate only", "estimate tokens", "scan"第7部分
检测到意图后,进入对应的部分。
终止条件(强制要求):
  • 若多个路由匹配或意图不明确:终止流程,请求用户选择一个路由。
  • 获得用户确认前,不得继续执行。
工作流价值: 基于研究的方法可在构建前验证设计。 带检查点的分步流程相比临时创建,可产出9.0/10以上的质量。

Section 2: Creation Workflows (Dual Mode)

第2部分:创建工作流(双模式)

Prerequisites: Skill description provided, workspace available.
前置条件: 已提供Skill描述,工作区可用。

Mode Selection (Required at Start)

模式选择(开始时必须进行)

Detect or prompt for workflow mode before running the creation flow.
Stop Condition (Mandatory):
  • If mode is not explicitly provided: stop and ask "Do you want fast or full mode?"
  • Do not continue until user confirms the mode.
ModeStepsValidationQuality TargetTime
fast10Structural only>=9.0/10<10 min
full14Structural + Behavioral>=9.0/10 and behavioral >=7.0<20 min
No implicit default mode is allowed when mode is not explicitly known.
在运行创建流程前,检测或提示用户选择工作流模式。
终止条件(强制要求):
  • 若未明确指定模式:终止流程并询问“您想要使用快速模式还是完整模式?”
  • 获得用户确认前,不得继续执行。
模式步骤数验证内容质量目标耗时
快速模式10仅结构验证>=9.0/10<10分钟
完整模式14结构+行为验证>=9.0/10且行为评分>=7.0<20分钟
当模式未明确时,不允许使用默认模式。

Workflow A: Fast Mode (10 Steps)

工作流A:快速模式(10步)

Use when
.skillkit-mode
contains
fast
or marker does not exist.
→ READ
references/section-2-fast-creation-workflow.md
IN FULL before starting.
Create a task for each step listed in that file, then follow them in order. The outline below is a summary only — the reference file is authoritative.
Phase 1: Decision & Research
  • Step 0: Decide approach (
    decision_helper.py
    )
  • Step 1: Research and proposals
  • Step 2: User validation
  • Stop Condition: Stop and request user approval before continuing to Step 3.
Phase 2: Creation
  • Step 3: Initialize skill (
    init.py skill <name> --mode fast
    )
  • Step 4: Create content
Phase 3: Structural Validation
  • Step 5: Validate skill (
    validate_skill.py
    ) — runs structure + security + tokens in one call
Phase 4: Packaging
  • Step 6: Progressive disclosure check
  • Step 7: Generate tests (
    test_generator.py
    )
  • Step 8: Quality assessment (
    quality_scorer.py
    )
  • Step 9: Package (
    package_skill.py
    )
.skillkit-mode
文件包含
fast
或不存在该文件时使用。
→ 开始前,请完整阅读
references/section-2-fast-creation-workflow.md
为该文件中列出的每个步骤创建任务,然后按顺序执行。 以下大纲仅为摘要——参考文件为权威依据。
阶段1:决策与研究
  • 步骤0:确定方法(
    decision_helper.py
  • 步骤1:研究与提案
  • 步骤2:用户验证
  • 终止条件:进入步骤3前,终止流程并请求用户批准。
阶段2:创建
  • 步骤3:初始化Skill(
    init.py skill <name> --mode fast
  • 步骤4:创建内容
阶段3:结构验证
  • 步骤5:验证Skill(
    validate_skill.py
    )——一次性运行结构、安全与Token验证
阶段4:打包
  • 步骤6:渐进式披露检查
  • 步骤7:生成测试用例(
    test_generator.py
  • 步骤8:质量评估(
    quality_scorer.py
  • 步骤9:打包(
    package_skill.py

Workflow B: Full Mode (14 Steps)

工作流B:完整模式(14步)

Use when
.skillkit-mode
contains
full
.
→ READ
references/section-2-full-creation-workflow.md
IN FULL before starting.
Create a task for each step listed in that file, then follow them in order. The outline below is a summary only — the reference file is authoritative.
Phase 1: Decision and Research
  • Step 0: Decide approach (
    decision_helper.py
    )
  • Step 1: Research and proposals
  • Step 2: User validation
  • Stop Condition: Stop and request user approval before continuing to Step 3.
Phase 2: Behavioral Baseline (extra vs fast)
  • Step 3 (RED): Run pressure scenarios without skill → Load
    references/section-2-full-creation-workflow.md
    → section "Full Mode Behavioral Testing Protocol" (mandatory)
  • Step 4: Document baseline failures
Phase 3: Creation
  • Step 5: Initialize skill (
    init.py skill <name> --mode full
    )
  • Step 6: Create content addressing baseline failures
Phase 4: Behavioral Verification (extra vs fast)
  • Step 7 (GREEN): Run scenarios with skill → Load
    references/section-2-full-creation-workflow.md
    → section "Full Mode Behavioral Testing Protocol" (mandatory)
  • Step 8: Fix gaps
Phase 5: Structural Validation
  • Step 9: Validate skill (
    validate_skill.py
    ) — runs structure + security + tokens in one call
Phase 6: Refinement (extra vs fast)
  • Step 10 (REFACTOR): Combined pressure tests → Load
    references/section-2-full-creation-workflow.md
    → section "Full Mode Behavioral Testing Protocol" (mandatory)
  • Step 11: Close loopholes
Phase 7: Packaging
  • Step 12: Quality assessment (
    quality_scorer.py --format json
    ) — behavioral score derived from Steps 3/7/10 subagent results, not from
    --behavioral
    flag
  • Step 13: Package (
    package_skill.py
    )
.skillkit-mode
文件包含
full
时使用。
→ 开始前,请完整阅读
references/section-2-full-creation-workflow.md
为该文件中列出的每个步骤创建任务,然后按顺序执行。 以下大纲仅为摘要——参考文件为权威依据。
阶段1:决策与研究
  • 步骤0:确定方法(
    decision_helper.py
  • 步骤1:研究与提案
  • 步骤2:用户验证
  • 终止条件:进入步骤3前,终止流程并请求用户批准。
阶段2:行为基准(相比快速模式新增)
  • 步骤3(红色阶段):在无Skill的情况下运行压力场景 → 加载
    references/section-2-full-creation-workflow.md
    → 章节“完整模式行为测试协议”(强制要求)
  • 步骤4:记录基准测试失败情况
阶段3:创建
  • 步骤5:初始化Skill(
    init.py skill <name> --mode full
  • 步骤6:创建解决基准测试失败问题的内容
阶段4:行为验证(相比快速模式新增)
  • 步骤7(绿色阶段):在有Skill的情况下运行场景 → 加载
    references/section-2-full-creation-workflow.md
    → 章节“完整模式行为测试协议”(强制要求)
  • 步骤8:修复漏洞
阶段5:结构验证
  • 步骤9:验证Skill(
    validate_skill.py
    )——一次性运行结构、安全与Token验证
阶段6:优化(相比快速模式新增)
  • 步骤10(重构阶段):组合压力测试 → 加载
    references/section-2-full-creation-workflow.md
    → 章节“完整模式行为测试协议”(强制要求)
  • 步骤11:填补漏洞
阶段7:打包
  • 步骤12:质量评估(
    quality_scorer.py --format json
    )——行为评分来自步骤3/7/10的Subagent结果,而非
    --behavioral
    参数
  • 步骤13:打包(
    package_skill.py

Mode Detection

模式检测

Priority order:
  1. Explicit flag:
    --mode fast
    or
    --mode full
  2. Skill marker:
    .skillkit-mode
    file content
  3. If unknown: stop and ask user to choose
    fast
    or
    full

优先级顺序:
  1. 显式参数:
    --mode fast
    --mode full
  2. Skill标记:
    .skillkit-mode
    文件内容
  3. 若未知:终止流程并询问用户选择
    fast
    full

Section 3: Validation Workflow (Overview)

第3部分:验证工作流(概述)

Use when: Validating existing skill
Steps: Execute validation subset (Steps 3-6)
  1. Validate skill — structure + security + tokens (
    validate_skill.py
    , no flags needed)
  2. Progressive disclosure check
  3. Test generation (optional)
  4. Quality assessment (quality_scorer.py)
Note:
--security-only
and
--tokens-only
flags are available for Section 7 individual tool use, not for workflow validation steps.
For detailed workflow: See references/section-3-validation-workflow-existing-skill.md

适用场景: 验证现有Skill
步骤: 执行验证子集(步骤3-6)
  1. 验证Skill —— 结构+安全+Token(
    validate_skill.py
    ,无需参数)
  2. 渐进式披露检查
  3. 生成测试用例(可选)
  4. 质量评估(
    quality_scorer.py
注意:
--security-only
--tokens-only
参数仅适用于第7部分的单一工具使用,不适用于工作流验证步骤。
详细工作流: 参考references/section-3-validation-workflow-existing-skill.md

Section 4: Decision Workflow (Overview)

第4部分:决策工作流(概述)

Use when: Uncertain if Skills is right approach
CRITICAL: Agent MUST create a temp JSON file first. The
decision_helper.py
script does NOT accept inline JSON strings - it requires a file path to a JSON file.
Step-by-step invocation: See
references/section-4-decision-workflow-skills-vs-subagents.md
Accuracy: Highest (90-95% confidence).
Process:
  1. Run
    decision_helper.py
    with json file.
  2. Answer interactive questions
  3. Receive recommendation with confidence score
  4. Proceed if Skills recommended (confidence >=75%)
  5. If confidence <75% or recommendation is uncertain, stop and ask user whether to continue, switch route, or refine inputs.
For detailed workflow: See references/section-4-decision-workflow-skills-vs-subagents.md

适用场景: 不确定是否应使用Skill的情况
关键要求:Agent必须先创建临时JSON文件。
decision_helper.py
脚本不接受内联JSON字符串——它需要指向JSON文件的路径。
分步调用说明: 参考
references/section-4-decision-workflow-skills-vs-subagents.md
准确率: 最高(90-95%置信度)。
流程:
  1. 使用JSON文件运行
    decision_helper.py
  2. 回答交互式问题
  3. 接收带置信度评分的推荐结果
  4. 若推荐使用Skill且置信度>=75%,则继续执行
  5. 若置信度<75%或推荐结果不确定,终止流程并询问用户是否继续、切换路由或优化输入。
详细工作流: 参考references/section-4-decision-workflow-skills-vs-subagents.md

Section 6: Subagent Creation Workflow (Overview)

第6部分:Subagent创建工作流(概述)

Use when: Creating new subagent (user explicitly asks or decision workflow recommends)
Prerequisites: Role definition clear, workspace available Quality Target: Clear role, comprehensive workflow, testable examples Time: <15 min with template
适用场景: 创建新Subagent(用户明确要求或决策工作流推荐)
前置条件: 角色定义清晰,工作区可用 质量目标: 角色明确、工作流全面、示例可测试 耗时: 使用模板时<15分钟

8-Step Process:

8步流程:

STEP 0: Requirements & Role Definition
  • Answer: Primary role? Trigger conditions? Tool requirements?
  • Choose subagent_type from predefined list
STEP 1: Initialize Subagent File
  • Tool:
    python scripts/init.py subagent subagent-name --path ~/.claude/agents
  • Creates:
    ~/.claude/agents/subagent-name.md
    with template
  • Important: Subagents are individual
    .md
    files (not directories)
  • Stop Condition: If target file already exists, stop and ask whether to overwrite, rename, or cancel.
STEP 2: Define Configuration
  • Edit YAML frontmatter (name, description, type, tools, skills)
  • Configure tool permissions (minimal but sufficient)
STEP 3: Define Role and Workflow
  • Role definition section
  • Trigger conditions (when to invoke)
  • Multi-phase workflow
STEP 4: Define Response Format
  • Output structure template
  • Tone and style guidelines
  • Error handling
STEP 5: Add Examples
  • At least 1 complete example
  • Input/Process/Output format
STEP 6: Validation
  • YAML validity check
  • Structure verification
  • Completeness review
STEP 7: Testing
  • Test invocation with Task tool
  • Iterate based on results
STEP 8: Documentation & Deployment
  • Create README.md
  • Register in system
  • Stop Condition: Ask for explicit user confirmation before register/deploy actions.
For detailed workflow: See references/section-6-subagent-creation-workflow.md

步骤0:需求与角色定义
  • 明确:主要角色?触发条件?工具需求?
  • 从预定义列表中选择subagent_type
步骤1:初始化Subagent文件
  • 工具:
    python scripts/init.py subagent subagent-name --path ~/.claude/agents
  • 创建:
    ~/.claude/agents/subagent-name.md
    文件(带模板)
  • 重要提示: Subagent是独立的
    .md
    文件(而非目录)
  • 终止条件:若目标文件已存在,终止流程并询问用户是否覆盖、重命名或取消。
步骤2:定义配置
  • 编辑YAML前置元数据(名称、描述、类型、工具、Skills)
  • 配置工具权限(最小但足够)
步骤3:定义角色与工作流
  • 角色定义章节
  • 触发条件(何时调用)
  • 多阶段工作流
步骤4:定义响应格式
  • 输出结构模板
  • 语气与风格指南
  • 错误处理
步骤5:添加示例
  • 至少1个完整示例
  • 输入/流程/输出格式
步骤6:验证
  • YAML有效性检查
  • 结构验证
  • 完整性审查
步骤7:测试
  • 使用Task工具调用测试
  • 根据结果迭代优化
步骤8:文档与部署
  • 创建README.md
  • 在系统中注册
  • 终止条件:注册/部署前,请求用户明确确认。
详细工作流: 参考references/section-6-subagent-creation-workflow.md

Section 5: Migration Workflow (Overview)

第5部分:迁移工作流(概述)

Use when: Converting document to skill
Process:
  1. Decision check (Step 0)
  2. Migration analysis (migration_helper.py)
  3. Structure creation
  4. Execute validation steps (5-8)
  5. Package (Step 9)
Stop Condition (Mandatory):
  • Before structure creation or any write/overwrite operation: ask user confirmation.
  • Do not modify files until user confirms.
For detailed workflow: See references/section-5-migration-workflow-doc-to-skill.md

适用场景: 将文档转换为Skill
流程:
  1. 决策检查(步骤0)
  2. 迁移分析(
    migration_helper.py
  3. 结构创建
  4. 执行验证步骤(5-8)
  5. 打包(步骤9)
终止条件(强制要求):
  • 在创建结构或执行任何写入/覆盖操作前:请求用户确认。
  • 获得用户确认前,不得修改文件。
详细工作流: 参考references/section-5-migration-workflow-doc-to-skill.md

Section 7: Individual Tool Usage

第7部分:单一工具使用

Use when: User needs single tool, not full workflow
Entry Point: User asks for specific tool like "estimate tokens" or "security scan"
适用场景: 用户仅需使用单个工具,而非完整工作流
入口: 用户请求特定工具,如“estimate tokens”或“security scan”

Available Tools

可用工具

Validation Tool:
bash
python scripts/validate_skill.py skill-name/ --format json
Guide:
knowledge/tools/14-validation-tools-guide.md
Token Estimator:
bash
python scripts/validate_skill.py skill-name/ --tokens-only --format json
Guide:
knowledge/tools/15-cost-tools-guide.md
Security Scanner:
bash
python scripts/validate_skill.py skill-name/ --security-only --format json
Guide:
knowledge/tools/16-security-tools-guide.md
Pattern Detector:
bash
undefined
验证工具:
bash
python scripts/validate_skill.py skill-name/ --format json
指南:
knowledge/tools/14-validation-tools-guide.md
Token估算工具:
bash
python scripts/validate_skill.py skill-name/ --tokens-only --format json
指南:
knowledge/tools/15-cost-tools-guide.md
安全扫描工具:
bash
python scripts/validate_skill.py skill-name/ --security-only --format json
指南:
knowledge/tools/16-security-tools-guide.md
模式检测工具:
bash
undefined

Analysis mode with JSON output

分析模式(JSON输出)

python scripts/pattern_detector.py "convert PDF to Word" --format json
python scripts/pattern_detector.py "convert PDF to Word" --format json

List all patterns

列出所有模式

python scripts/pattern_detector.py --list --format json
python scripts/pattern_detector.py --list --format json

Interactive mode (text only)

交互模式(仅文本)

python scripts/pattern_detector.py --interactive
Guide: `knowledge/tools/17-pattern-tools-guide.md`

**Decision Helper:**
```bash
python scripts/pattern_detector.py --interactive
指南:`knowledge/tools/17-pattern-tools-guide.md`

**决策辅助工具:**
```bash

Analyze use case (JSON output - agent-layer default)

分析用例(JSON输出 - Agent层默认)

python scripts/decision_helper.py --analyze "code review with validation"
python scripts/decision_helper.py --analyze "code review with validation"

Show decision criteria (JSON output)

显示决策标准(JSON输出)

python scripts/decision_helper.py --show-criteria --format json
python scripts/decision_helper.py --show-criteria --format json

Text mode for human reading (debugging)

人类可读文本模式(调试用)

python scripts/decision_helper.py --analyze "description" --format text
Guide: `knowledge/tools/18-decision-helper-guide.md`

**Test Generator (v1.2: Parameter update):**
```bash
python scripts/test_generator.py skill-name/ --test-format pytest --format json
  • --test-format
    : Test framework (pytest/unittest/plain, default: pytest)
  • --format
    : Output style (text/json, default: text)
  • Backward compatible: Old
    --output
    parameter still works (deprecated)
Guide:
knowledge/tools/19-test-generator-guide.md
Split Skill:
bash
python scripts/split_skill.py skill-name/ --format json
Guide:
knowledge/tools/20-split-skill-guide.md
Quality Scorer:
bash
python scripts/quality_scorer.py skill-name/ --format json
Guide:
knowledge/tools/21-quality-scorer-guide.md
Migration Helper:
bash
python scripts/migration_helper.py doc.md --format json
Guide:
knowledge/tools/22-migration-helper-guide.md
Subagent Initializer (NEW):
bash
python scripts/init.py subagent subagent-name --path /path/to/subagents
Guide:
references/section-6-subagent-creation-workflow.md
python scripts/decision_helper.py --analyze "description" --format text
指南:`knowledge/tools/18-decision-helper-guide.md`

**测试生成工具(v1.2:参数更新):**
```bash
python scripts/test_generator.py skill-name/ --test-format pytest --format json
  • --test-format
    :测试框架(pytest/unittest/plain,默认:pytest)
  • --format
    :输出格式(text/json,默认:text)
  • 向后兼容:旧参数
    --output
    仍可使用(已废弃)
指南:
knowledge/tools/19-test-generator-guide.md
Skill拆分工具:
bash
python scripts/split_skill.py skill-name/ --format json
指南:
knowledge/tools/20-split-skill-guide.md
质量评分工具:
bash
python scripts/quality_scorer.py skill-name/ --format json
指南:
knowledge/tools/21-quality-scorer-guide.md
迁移辅助工具:
bash
python scripts/migration_helper.py doc.md --format json
指南:
knowledge/tools/22-migration-helper-guide.md
Subagent初始化工具(新增):
bash
python scripts/init.py subagent subagent-name --path /path/to/subagents
指南:
references/section-6-subagent-creation-workflow.md

Tool Output Standardization (v1.0.1+)

工具输出标准化(v1.0.1+)

All 9 tools support
--format json
. Text mode still available via
--format text
(backward compatible).
decision_helper
defaults to JSON for automation.
JSON Output Structure:
json
{
  "status": "success" | "error",
  "tool": "tool_name",
  "timestamp": "ISO-8601",
  "data": { /* tool-specific results */ }
}
所有9个工具均支持
--format json
。文本模式仍可通过
--format text
使用(向后兼容)。
decision_helper
默认使用JSON格式以支持自动化。
JSON输出结构:
json
{
  "status": "success" | "error",
  "tool": "tool_name",
  "timestamp": "ISO-8601",
  "data": { /* 工具特定结果 */ }
}

Quality Assurance Enhancements (v1.2+)

质量保证增强(v1.2+)

File & Reference Validation:
  • validate_skill.py
    now comprehensively checks file references (markdown links, code refs, path patterns)
  • package_skill.py
    validates references before packaging, detects orphaned files
  • Prevents broken references and incomplete files in deployed skills
Content Budget Enforcement (v1.2+):
  • Hard limits on file size: P0 ≤150 lines, P1 ≤100 lines, P2 ≤60 lines
  • Real-time token counting with progress indicators
  • Prevents file bloat that previously caused 4-9x target overruns
Execution Planning (v1.2+):
  • P0/P1/P2 prioritization prevents over-scoping
  • Token budget allocated per file to maintain efficiency
  • Research phase respects Verbalized Sampling probability thresholds (p>0.10)
Quality Scorer Context:
  • Scores calibrated for general skill quality heuristics
  • Target: 70%+ is good, 80%+ is excellent
  • Style scoring may not fit all skill types (educational vs technical)
  • Use as guidance, supplement with manual review for edge cases

文件与引用验证:
  • validate_skill.py
    现在可全面检查文件引用(Markdown链接、代码引用、路径模式)
  • package_skill.py
    在打包前验证引用,检测孤立文件
  • 防止已部署Skill中出现无效引用和不完整文件
内容预算管控(v1.2+):
  • 文件大小硬限制:P0 ≤150行,P1 ≤100行,P2 ≤60行
  • 带进度指示器的实时Token计数
  • 防止之前导致4-9倍目标超限的文件膨胀问题
执行规划(v1.2+):
  • P0/P1/P2优先级划分可防止范围过度扩大
  • 为每个文件分配Token预算以保持效率
  • 研究阶段遵循Verbalized Sampling概率阈值(p>0.10)
质量评分工具说明:
  • 评分基于通用Skill质量启发式算法校准
  • 目标:70%+为良好,80%+为优秀
  • 风格评分可能不适用于所有Skill类型(教育类vs技术类)
  • 用作指导,针对边缘情况需补充人工审查

Section 8: Mode Selection Guide

第8部分:模式选择指南

Skill TypeRecommended ModeWhy
TDD or discipline skillfullmust resist rationalization under pressure
Code pattern skillfaststructural checks are usually sufficient
API reference skillfastprimarily retrieval accuracy
Workflow orchestration skillfullcomplex flow benefits from pressure checks
Debugging technique skillfastconcise technique with clear method
Full mode adds behavioral testing (pressure scenarios). Use it when discipline enforcement is core to the skill's purpose.

Skill类型推荐模式原因
TDD或纪律类Skill完整模式必须能在压力下抵制合理化行为
代码模式类Skill快速模式结构检查通常已足够
API参考类Skill快速模式主要关注检索准确性
工作流编排类Skill完整模式复杂流程可从压力测试中获益
调试技巧类Skill快速模式技巧简洁、方法明确
完整模式新增行为测试(压力场景)。当纪律执行为Skill核心目标时使用。

Section 9: Knowledge Reference Map (Overview)

第9部分:知识参考地图(概述)

Strategic context loaded on-demand.
战略上下文按需加载。

Foundation Concepts (Files 01-08):

基础概念(文件01-08):

  • Why Skills exist vs alternatives
  • Skills vs Subagents decision framework
  • Token economics and efficiency
  • Platform constraints and security
  • When NOT to use Skills
  • Skill存在的原因与替代方案对比
  • Skill vs Subagent决策框架
  • Token经济与效率
  • 平台约束与安全
  • 不适合使用Skill的场景

Application Knowledge (Files 09-13):

应用知识(文件09-13):

  • Real-world case studies (Rakuten, Box, Notion)
  • Technical architecture patterns
  • Adoption and testing strategies
  • Competitive landscape analysis
  • 真实案例研究(乐天、Box、Notion)
  • 技术架构模式
  • 采用与测试策略
  • 竞争格局分析

Tool Guides (Files 14-22):

工具指南(文件14-22):

  • One guide per automation script
  • Usage patterns and parameters
  • JSON output formats
  • Integration examples
For complete reference map: See references/section-7-knowledge-reference-map.md

  • 每个自动化脚本对应一份指南
  • 使用模式与参数
  • JSON输出格式
  • 集成示例
完整参考地图: 参考references/section-7-knowledge-reference-map.md

Workflow Compliance

工作流合规性

Follow workflows sequentially. Sequential steps with gates produce 9.0/10+ quality. Deviations are allowed with user justification.
Flexible entry points:
  • Single tool (Section 7): skip full workflow
  • Validation only (Section 3): run validation subset
  • Subagent (Section 6): streamlined 8-step workflow

按顺序执行工作流。带检查点的分步流程可产出9.0/10以上的质量。经用户说明后可允许偏离。
灵活入口点:
  • 单一工具(第7部分):跳过完整工作流
  • 仅验证(第3部分):运行验证子集
  • Subagent(第6部分):简化的8步工作流

Additional Resources

附加资源

Load reference files on-demand from
references/
when detailed implementation guidance is needed.
当需要详细实现指导时,从
references/
目录按需加载参考文件。