Agent Skills: Documentation Creation Specialist - Unified Markdown & Component Management

Documentation Creation Specialist - Unified Markdown & Component Management

Unified specialist providing: (1) Document quality pipeline with structure enforcement and content optimization, (2) OpenCode component creation (skills, agents, commands) with scaffolding, validation and packaging, (3) ASCII flowchart creation for visualizing workflows and (4) Install guide creation for setup documentation.

Core Principle: Structure first, then content, then quality.

Architecture: Scripts handle deterministic parsing/metrics. AI handles quality judgment and recommendations.

1. WHEN TO USE

Use Case: Document Quality Management

Enforce markdown structure, optimize content for AI assistants, validate quality through script-assisted AI analysis.

README Creation - Use readme_template.md when:

• Creating new README for any folder or project
• User requests "create a README", "add documentation"
• Folder needs comprehensive documentation

Frontmatter Validation - Use frontmatter_templates.md when:

• Validating YAML frontmatter in any document
• Checking required fields for document types
• Fixing frontmatter syntax errors

Validation Workflow - Apply after Write/Edit operations:

• Auto-correct filename violations (ALL CAPS to lowercase, hyphens to underscores)
• Fix safe violations (separators, H2 case)
• Check critical violations (missing frontmatter, wrong section order)

Manual Optimization - Run when:

• README needs optimization for AI assistants
• Creating critical documentation (specs, knowledge, skills)
• Pre-release quality checks
• Generating llms.txt for LLM navigation

Use Case: OpenCode Component Creation

Create and manage OpenCode components (skills, agents, commands). Each component type has templates and validation with quality standards.

Component Types:

• Skills (.opencode/skill/) - Knowledge bundles with workflows → skill_creation.md
• Agents (.opencode/agent/) - AI personas with tool permissions → agent_template.md
• Commands (.opencode/command/) - Slash commands for user invocation → command_template.md

For larger skills, split deep content into focused references/ files and keep concise navigation in SKILL.md or README.md.

Start with: skill_creation.md (Section 9) Primary templates:

• skill_md_template.md
• skill_reference_template.md
• skill_asset_template.md

Use when:

• User requests skill creation ("create a skill", "make a new skill")
• User requests agent creation ("create an agent", "make a new agent")
• User requests command creation ("create a command", "add a slash command")
• Scaffolding component structure
• Validating component quality
• Packaging skill for distribution

Skill Process (6 steps): Understanding (examples) → Planning (resources) → Initialization (init_skill.py) → Editing (populate) → Packaging (package_skill.py) → Iteration (test/improve)

Agent Process: Load agent_template.md → Define frontmatter (tools, permissions) → Create sections (workflow, capabilities, anti-patterns) → Validate → Test

Command Process: Load command_template.md → Define frontmatter (name, description) → Create execution logic → Add to command registry → Test

Use Case: Flowchart Creation

Create ASCII flowcharts for visualizing workflows, user journeys and decision trees.

For styled HTML visuals (interactive diagrams, dashboard pages, or polished data-table renders), route to sk-doc-visual instead of forcing ASCII/markdown flowcharts.

Use when:

• Documenting multi-step processes with branching
• Creating decision trees with multiple outcomes
• Showing parallel execution with sync points
• Visualizing approval gates and revision cycles

See: assets/flowcharts/

Use Case: Install Guide Creation

Create and validate installation documentation for MCP servers, plugins and tools using phase-based templates.

Use when:

• Creating documentation for MCP server installation
• Documenting plugin setup procedures
• Standardizing tool installation across platforms
• Need phase-based validation checkpoints

5-Phase Process: Overview → Prerequisites → Installation → Configuration → Verification

See: install_guide_standards.md

When NOT to Use (All Modes)

• Non-markdown files (only .md supported)
• Simple typo fixes (use Edit tool directly)
• Internal notes or drafts
• Auto-generated API docs
• Short 2-3 step processes (use bullet points)

2. SMART ROUTING

Resource Domains

The router discovers markdown resources recursively from references/ and assets/ and then applies intent scoring from RESOURCE_MAP. Keep this section domain-focused rather than static file inventories.

• references/ for documentation standards, validation rules, optimization guidance, and execution workflows.
• assets/documentation/ for README, frontmatter, llms.txt, and install-guide templates.
• assets/opencode/ for skill, agent, and command creation templates.
• assets/flowcharts/ for reusable ASCII flowchart patterns and diagram examples.

Resource Loading Levels

| Level | When to Load | Resources | | ----------- | ------------------------ | --------------------------- | | ALWAYS | Every skill invocation | Quick reference baseline | | CONDITIONAL | If intent signals match | Mode-specific docs/templates| | ON_DEMAND | Only on explicit request | Extended standards/template |

Smart Router Pseudocode

The authoritative routing logic for scoped loading, weighted intent scoring, and ambiguity handling.

from pathlib import Path

SKILL_ROOT = Path(__file__).resolve().parent
RESOURCE_BASES = (SKILL_ROOT / "references", SKILL_ROOT / "assets")
DEFAULT_RESOURCE = "references/quick_reference.md"

INTENT_SIGNALS = {
    "DOC_QUALITY": {"weight": 4, "keywords": ["dqi", "quality", "validate", "extract_structure"]},
    "OPTIMIZATION": {"weight": 3, "keywords": ["optimize", "llms.txt", "ai context"]},
    "SKILL_CREATION": {"weight": 4, "keywords": ["skill creation", "new skill", "init_skill", "package_skill"]},
    "AGENT_COMMAND": {"weight": 4, "keywords": ["create agent", "create command", "agent template", "command template"]},
    "FLOWCHART": {"weight": 3, "keywords": ["flowchart", "ascii diagram", "decision tree", "swimlane"]},
    "INSTALL_GUIDE": {"weight": 3, "keywords": ["install guide", "setup instructions", "prerequisite"]},
    "HVR": {"weight": 4, "keywords": ["human voice", "hvr", "voice rules", "banned words", "writing style"]},
}

RESOURCE_MAP = {
    "DOC_QUALITY": ["references/validation.md", "references/workflows.md", "references/core_standards.md"],
    "OPTIMIZATION": ["references/optimization.md", "assets/documentation/llmstxt_templates.md"],
    "SKILL_CREATION": ["references/skill_creation.md", "assets/opencode/skill_md_template.md", "assets/opencode/skill_reference_template.md"],
    "AGENT_COMMAND": ["assets/opencode/agent_template.md", "assets/opencode/command_template.md"],
    "FLOWCHART": ["assets/flowcharts/simple_workflow.md", "assets/flowcharts/decision_tree_flow.md"],
    "INSTALL_GUIDE": ["assets/documentation/install_guide_template.md", "references/install_guide_standards.md"],
    "HVR": ["references/hvr_rules.md"],
}

LOADING_LEVELS = {
    "ALWAYS": [DEFAULT_RESOURCE],
    "ON_DEMAND_KEYWORDS": ["full standards", "all templates", "deep dive"],
    "ON_DEMAND": ["assets/documentation/readme_template.md", "assets/documentation/frontmatter_templates.md"],
}

def _task_text(task) -> str:
    return " ".join([
        str(getattr(task, "text", "")),
        str(getattr(task, "query", "")),
        " ".join(getattr(task, "keywords", []) or []),
    ]).lower()

def _guard_in_skill(relative_path: str) -> str:
    resolved = (SKILL_ROOT / relative_path).resolve()
    resolved.relative_to(SKILL_ROOT)
    if resolved.suffix.lower() != ".md":
        raise ValueError(f"Only markdown resources are routable: {relative_path}")
    return resolved.relative_to(SKILL_ROOT).as_posix()

def discover_markdown_resources() -> set[str]:
    docs = []
    for base in RESOURCE_BASES:
        if base.exists():
            docs.extend(p for p in base.rglob("*.md") if p.is_file())
    return {doc.relative_to(SKILL_ROOT).as_posix() for doc in docs}

def score_intents(task) -> dict[str, float]:
    """Weighted intent scoring from request text and documentation modes."""
    text = _task_text(task)
    scores = {intent: 0.0 for intent in INTENT_SIGNALS}
    for intent, cfg in INTENT_SIGNALS.items():
        for keyword in cfg["keywords"]:
            if keyword in text:
                scores[intent] += cfg["weight"]
    return scores

def select_intents(scores: dict[str, float], ambiguity_delta: float = 1.0, max_intents: int = 2) -> list[str]:
    ranked = sorted(scores.items(), key=lambda item: item[1], reverse=True)
    if not ranked or ranked[0][1] <= 0:
        return ["DOC_QUALITY"]
    selected = [ranked[0][0]]
    if len(ranked) > 1 and ranked[1][1] > 0 and (ranked[0][1] - ranked[1][1]) <= ambiguity_delta:
        selected.append(ranked[1][0])
    return selected[:max_intents]

def route_documentation_resources(task):
    inventory = discover_markdown_resources()
    intents = select_intents(score_intents(task), ambiguity_delta=1.0)
    loaded = []
    seen = set()

    def load_if_available(relative_path: str) -> None:
        guarded = _guard_in_skill(relative_path)
        if guarded in inventory and guarded not in seen:
            load(guarded)
            loaded.append(guarded)
            seen.add(guarded)

    for relative_path in LOADING_LEVELS["ALWAYS"]:
        load_if_available(relative_path)
    for intent in intents:
        for relative_path in RESOURCE_MAP.get(intent, []):
            load_if_available(relative_path)

    text = _task_text(task)
    if any(keyword in text for keyword in LOADING_LEVELS["ON_DEMAND_KEYWORDS"]):
        for relative_path in LOADING_LEVELS["ON_DEMAND"]:
            load_if_available(relative_path)

    if not loaded:
        load_if_available(DEFAULT_RESOURCE)

    return {"intents": intents, "resources": loaded}

3. HOW IT WORKS

Mode 1: Document Quality

Script-Assisted AI Analysis:

# 1. Extract document structure to JSON
scripts/extract_structure.py path/to/document.md

# 2. AI receives JSON with:
#    - Frontmatter, structure, metrics
#    - Checklist results, DQI score
#    - Evaluation questions

# 3. AI reviews and provides recommendations

Document Type Detection (auto-applies enforcement):

| Type | Enforcement | Frontmatter | Notes | | --------- | ----------- | ----------- | -------------------------------- | | README | Flexible | None | Focus on quick-start usability | | SKILL | Strict | Required | No structural checklist failures | | Knowledge | Moderate | Forbidden | Consistent, scannable reference | | Command | Strict | Required | Must be executable | | Spec | Loose | Optional | Working docs. Avoid blocking. | | Generic | Flexible | Optional | Best-effort structure |

Mode 2: OpenCode Component Creation

Skill Creation

Progressive Disclosure Design:

1. Metadata (name + description) - Always in context (~100 words)

2. SKILL.md body - When skill triggers (<5k words)

3. Bundled resources - As needed (unlimited)

4. Define scope using skill_creation.md (Section 9)

5. Use skill_reference_template.md to keep supplemental docs consistent

After packaging: Run extract_structure.py on SKILL.md for final quality review.

Typical Workflow:

# 1. Initialize skill structure
scripts/init_skill.py my-skill --path .opencode/skill

# 2. Edit SKILL.md and bundled resources
# [User populates templates with content]

# 3. Quick validation check
scripts/quick_validate.py .opencode/skill/my-skill --json

# 4. Package with full validation
scripts/package_skill.py .opencode/skill/my-skill

# 5. Quality assurance (DQI scoring)
scripts/extract_structure.py .opencode/skill/my-skill/SKILL.md

Agent Creation

Template-First Workflow:

1. Load agent_template.md for structure reference
2. Create agent file in .opencode/agent/
3. Define YAML frontmatter (name, tools, permissions)
4. Create required sections (workflow, capabilities, anti-patterns)
5. Validate frontmatter syntax
6. Test with real examples

Key Difference from Skills: Agents have tool permissions (true/false per tool) and action permissions (allow/deny), not an allowed-tools array.

Command Creation

Template-First Workflow:

1. Load command_template.md for structure reference
2. Create command file in .opencode/command/
3. Define YAML frontmatter (name, description, triggers)
4. Create execution logic and examples
5. Add to command registry
6. Test invocation

Mode 3: Flowchart Creation

Building Blocks:

Process Box:        Decision Diamond:     Terminal:
┌─────────────┐         ╱──────╲           ╭─────────╮
│   Action    │        ╱ Test?  ╲          │  Start  │
└─────────────┘        ╲        ╱          ╰─────────╯
                        ╲──────╱

Flow Control:

Standard Flow:      Branch:           Parallel:         Merge:
     │              │   │   │         ┌────┬────┐         │
     ▼              ▼   ▼   ▼         │    │    │      ───┴───
                                      ▼    ▼    ▼         │

7 Core Patterns:

| Pattern | Use Case | Reference File | | -------------------- | ------------------------------ | --------------------------------- | | 1: Linear Sequential | Step-by-step without branching | simple_workflow.md | | 2: Decision Branch | Binary or multi-way decisions | decision_tree_flow.md | | 3: Parallel | Multiple tasks run together | parallel_execution.md | | 4: Nested | Embedded sub-workflows | user_onboarding.md | | 5: Approval Gate | Review/approval required | approval_workflow_loops.md | | 6: Loop/Iteration | Repeat until condition met | approval_workflow_loops.md | | 7: Pipeline | Sequential stages with gates | system_architecture_swimlane.md |

Workflow: Select pattern → Build with components → Validate (validate_flowchart.sh) → Document

4. RULES

✅ Mode 1: Document Quality

✅ ALWAYS

1. ALWAYS validate filename conventions (snake_case, preserve README.md/SKILL.md)
2. ALWAYS detect document type first (applies correct enforcement level)
3. ALWAYS verify frontmatter for SKILL.md and Command types
4. NEVER add TOC (only allowed in README files)
5. ALWAYS ask about llms.txt generation (never auto-generate)
6. ALWAYS apply safe auto-fixes (H2 case, separators, filenames)
7. ALWAYS validate before completion (structure + content + style)
8. ALWAYS provide metrics (before/after counts from script output)
9. ALWAYS run validate_document.py before delivery (exit 0 required for READMEs)
10. ALWAYS enforce Human Voice Rules (HVR) on all documentation output. Full ruleset: hvr_rules.md. Quick reference: readme_template.md §9.

❌ NEVER

1. NEVER modify spec files during active development (loose enforcement)
2. NEVER delete original content without approval
3. NEVER block for safe violations (only block: missing frontmatter, wrong order)
4. NEVER generate llms.txt without asking
5. NEVER apply wrong enforcement level
6. NEVER use banned HVR words (leverage, robust, seamless, ecosystem, utilize, holistic, curate, harness, elevate, foster, empower, landscape, groundbreaking, cutting-edge, delve, illuminate, innovative, remarkable)

⚠️ ESCALATE IF

1. Document type ambiguous
2. Critical violations detected
3. Major restructuring needed
4. Style guide missing
5. Conflicts with user intent

Mode 2: OpenCode Component Creation

Skills

✅ ALWAYS

1. ALWAYS start with concrete examples (validate understanding)
2. ALWAYS run init_skill.py (proper scaffolding)
3. ALWAYS identify bundled resources (scripts/references/assets)
4. ALWAYS include a REFERENCES section (or combined SMART ROUTING & REFERENCES) for packaging compatibility
5. ALWAYS use third-person ("Use when..." not "You should use...")
6. ALWAYS keep SKILL.md <5k words (move details to references/)
7. ALWAYS delete unused examples (keep lean)
8. ALWAYS validate before packaging
9. ALWAYS recommend final review (run extract_structure.py)

❌ NEVER

1. NEVER use second-person (imperative/infinitive only)
2. NEVER duplicate SKILL.md/references/ (progressive disclosure)
3. NEVER create without examples
4. NEVER skip validation
5. NEVER include excessive detail (SKILL.md is orchestrator)
6. NEVER use vague descriptions

⚠️ ESCALATE IF

1. Skill purpose unclear
2. No concrete examples
3. Validation fails repeatedly
4. Unsupported features
5. User input required (brand assets, API docs)

Agents

✅ ALWAYS

1. ALWAYS load agent_template.md first (template-first workflow)
2. ALWAYS validate frontmatter (name, mode, temperature, tools, permission)
3. ALWAYS include CORE WORKFLOW section (numbered steps)
4. ALWAYS include ANTI-PATTERNS section (what NOT to do)
5. ALWAYS set explicit tool permissions (true/false for each tool)
6. ALWAYS test with real examples before deployment

❌ NEVER

1. NEVER create agents without @write agent (bypasses quality gates)
2. NEVER skip frontmatter validation (causes discovery failures)
3. NEVER use vague tool permissions (be explicit: true or false)
4. NEVER omit anti-patterns (agents need clear boundaries)

⚠️ ESCALATE IF

1. Agent purpose overlaps with existing agent
2. Tool permissions unclear
3. Behavioral rules conflict with AGENTS.md

Commands

✅ ALWAYS

1. ALWAYS load command_template.md first (template-first workflow)
2. ALWAYS define clear triggers (what invokes the command)
3. ALWAYS include usage examples (copy-paste ready)
4. ALWAYS validate command name (lowercase, colon-separated)

❌ NEVER

1. NEVER create commands without frontmatter (required for discovery)
2. NEVER use ambiguous triggers (must be unique)
3. NEVER skip testing (commands must work on first invocation)

⚠️ ESCALATE IF

1. Command conflicts with existing command
2. Trigger phrase is ambiguous
3. Command requires special permissions

Mode 3: Flowchart Creation

✅ ALWAYS

1. ALWAYS use consistent box styles (single-line process, rounded terminals, diamond decisions)
2. ALWAYS label all decision branches (Yes/No or specific outcomes)
3. ALWAYS align elements (no diagonal lines, consistent spacing)
4. ALWAYS show complete paths (every box has entry/exit)
5. ALWAYS validate readability

❌ NEVER

1. NEVER create ambiguous arrow connections
2. NEVER leave decision outcomes unlabeled
3. NEVER exceed 40 boxes (break into sub-workflows)
4. NEVER mix box styles inconsistently
5. NEVER skip spacing and alignment

⚠️ ESCALATE IF

1. Process exceeds ~40 boxes
2. Interactive/exportable format needed
3. Collaborative editing required
4. Pattern unclear

Mode 4: Install Guide Creation

✅ ALWAYS

1. ALWAYS include AI-first install prompt at the top
2. ALWAYS use phase validation checkpoints (phase_N_complete pattern)
3. ALWAYS provide platform-specific configurations (OpenCode, Claude Code, Claude Desktop)
4. ALWAYS include troubleshooting section with Error → Cause → Fix format
5. ALWAYS verify commands are copy-paste ready

❌ NEVER

1. NEVER skip validation checkpoints (each phase must validate)
2. NEVER assume prerequisites (always list and verify)
3. NEVER mix platform instructions (separate clearly)
4. NEVER use relative paths in command examples

⚠️ ESCALATE IF

1. Multi-platform complexity requires testing
2. External dependencies unavailable
3. Installation requires special permissions

5. REFERENCES

Core References

• core_standards.md - markdown structure standards and naming conventions
• validation.md - validation pipeline and blocking criteria
• workflows.md - execution workflows by documentation mode
• skill_creation.md - skill lifecycle and packaging guidance

Templates

• skill_md_template.md - canonical SKILL.md template
• readme_template.md - README structure and quality rules
• install_guide_template.md - install guide template

Validation Scripts

• scripts/validate_document.py
• scripts/extract_structure.py
• scripts/package_skill.py

6. SUCCESS CRITERIA

Document Quality Index (DQI)

The extract_structure.py script computes a DQI (0-100) based on measurable attributes:

| Component | Max | Measures | | ------------- | --- | ------------------------------------------------- | | Structure | 40 | Checklist pass rate (type-specific) | | Content | 30 | Word count, heading density, code examples, links | | Style | 30 | H2 formatting, dividers, intro paragraph, HVR compliance |

HVR Compliance in DQI: Human Voice Rules violations count against the Style component. Documents with em dashes, semicolons, banned words or banned phrases receive deductions in the Style score. Full HVR ruleset: hvr_rules.md.

Quality Bands:

| Band | Score | Action | | -------------- | ------ | --------------------------------- | | Excellent | 90-100 | None needed | | Good | 75-89 | Minor improvements | | Acceptable | 60-74 | Several areas need attention | | Needs Work | <60 | Significant improvements required |

Example DQI Output (from extract_structure.py):

{
  "dqi": {
    "total": 96,
    "band": "excellent",
    "components": {
      "structure": 40,
      "content": 26,
      "style": 30
    }
  },
  "checklist": { "passed": 12, "failed": 0, "skipped": 2 },
  "documentType": "SKILL"
}

Completion Checklists

Document Quality Complete:

• ✅ extract_structure.py executed, JSON parsed
• ✅ Document type detected, checklist reviewed
• ✅ Evaluation questions answered, recommendations generated
• ✅ All critical issues addressed
• ✅ HVR compliance verified (no banned words, punctuation or structure violations)

Skill Creation Complete:

• ✅ YAML frontmatter with name + description (third-person, specific)
• ✅ SKILL.md under 5k words, bundled resources organized
• ✅ Unused examples deleted, passes package_skill.py
• ✅ Final AI review completed, tested on real examples

Agent Creation Complete:

• ✅ YAML frontmatter with name, mode, temperature, tools, permission
• ✅ Tool permissions explicitly set (true/false for each)
• ✅ CORE WORKFLOW section with numbered steps
• ✅ ANTI-PATTERNS section with clear boundaries
• ✅ RELATED RESOURCES section with links
• ✅ Tested with real examples

Command Creation Complete:

• ✅ YAML frontmatter with name, description, triggers
• ✅ Clear usage examples (copy-paste ready)
• ✅ Execution logic defined
• ✅ Added to command registry
• ✅ Tested invocation works

Flowchart Complete:

• ✅ All paths clear, decisions labeled, parallel blocks resolve
• ✅ Spacing consistent, understandable without explanation
• ✅ Size limits: ≤40 boxes, ≤8 depth levels, ≤200 lines

Install Guide Complete:

• ✅ AI-first prompt included, copy-paste ready
• ✅ All 5 phases have validation checkpoints
• ✅ Platform configurations provided (at least OpenCode)
• ✅ Troubleshooting covers common errors
• ✅ Commands tested and working

Document-Type Gates

| Type | Structure | Content | Required | | --------- | ----------------------- | -------------------- | --------------------------- | | SKILL.md | Strict (no failures) | High AI-friendliness | Frontmatter, WHEN/SMART/HOW/RULES/REFERENCES | | README.md | Flexible | High AI-friendliness | Quick Start, examples | | Knowledge | Strict (no frontmatter) | Good AI-friendliness | Numbered H2s |

7. INTEGRATION POINTS

Framework Integration

This skill operates within the behavioral framework defined in AGENTS.md.

Key integrations:

• Gate 2: Skill routing via skill_advisor.py
• Tool Routing: Per AGENTS.md Section 6 decision tree
• Memory: Context preserved via Spec Kit Memory MCP

Scripts

| Script | Purpose | Usage | | ----------------------- | ------------------------- | ------------------------------------------- | | validate_document.py | README format validation | scripts/validate_document.py doc.md | | extract_structure.py | Parse document to JSON | scripts/extract_structure.py doc.md | | init_skill.py | Scaffold skill structure | scripts/init_skill.py <name> --path <dir> | | package_skill.py | Validate + package to zip | scripts/package_skill.py <skill-path> | | quick_validate.py | Fast validation checks | scripts/quick_validate.py <skill-path> | | validate_flowchart.sh | Flowchart validation | scripts/validate_flowchart.sh <file> |

Tool Usage

| Tool | Purpose | | --------- | ---------------------------------------- | | Read | Examine files before optimization | | Write | Create optimized versions or llms.txt | | Edit | Apply specific transformations | | Bash | Execute scripts | | Glob | Find markdown files for batch processing | | Grep | Search for patterns/violations |

Related Skills

| Skill | Integration | | ------------------- | ----------------------------------------------------------------------------- | | system-spec-kit | Context files can be optimized. Validates spec folder documentation structure. | | sk-git | Uses documentation quality for commit/PR descriptions | | sk-doc-visual | Owns self-contained HTML visual outputs and interactive diagram rendering workflows. |

Workflow Integration

Skill Creation → Document Quality:

1. Initialize (init_skill.py)
2. Edit SKILL.md and resources
3. Package (package_skill.py)
4. Quality validation (extract_structure.py)
5. Iterate if needed

8. EXTERNAL RESOURCES

• llms.txt specification: https://llmstxt.org/
• Context7 (external docs benchmark): https://context7.ai/
• Anthropic documentation: https://docs.anthropic.com/
• CommonMark specification: https://spec.commonmark.org/

9. RELATED RESOURCES

For Document Quality

1. Read Sections 1-4 for activation, routing, workflow and rules.
2. Use Section 5 for canonical references and templates.
3. Navigate: workflows.md for execution modes.
4. Run enforcement, optimization, or validation as needed.

For Skill Creation

1. Read Sections 1-4 for activation, routing, workflow and rules.
2. Use Section 5 for canonical references and templates.
3. Navigate: skill_creation.md for workflow.
4. For layered skills, use skill_creation.md (Section 9).
5. Use templates: skill_md_template.md, skill_reference_template.md, skill_asset_template.md.
6. Use scripts: init_skill.py -> edit -> package_skill.py.
7. Validate: run Document Quality validation on SKILL.md.

Quick Reference

Need fast navigation? See quick_reference.md

Remember: This skill operates in four modes: Document Quality, Skill Creation, Flowchart Creation and Install Guide Creation. All modes integrate smoothly for creating and validating high-quality documentation and skills.