Deep Knowledge Skill Creator

Convert documentation repositories into comprehensive, well-structured skills through systematic multi-phase investigation using agent teams.

When to Use

• Creating skills from documentation repos (e.g., Microsoft docs, API references)
• Encoding organizational knowledge into reusable skills
• Systematic analysis of large codebases or documentation sets
• Refreshing/updating existing knowledge-based skills

Output Structure

skills/<skill-name>/
├── SKILL.md                              # Parent skill (generated in Phase 4)
├── investigation-reports/                # Phases 1-3 output
│   ├── repository-layout/                # Phase 1: Repo structure analysis
│   ├── feature-overview/                 # Phase 2: Feature discovery
│   └── feature-in-depth/                 # Phase 3: Comprehensive research
├── feature-area-skill-resources/         # Phase 4: Skill content by feature
│   ├── <feature-area-1>/
│   │   └── *.md
│   ├── <feature-area-2>/
│   │   └── *.md
│   └── ...
├── submodules/<submodule-1>/             # Git submodule repo 1 containing helpful information
└── submodules/<submodule-1>/             # Git submodule repo 2 containing helpful information

Workflow Overview

Phase 0: Submodule Setup
    │
    ▼
Phase 1: Repository Layout Analysis
    │   (Agent team crawls submodule, documents structure)
    ▼
Phase 2: Feature Overview Discovery
    │   (Agent team identifies ALL features/sub-features)
    ▼
Phase 3: Feature In-Depth Research  ◄──────────────────┐
    │   (Agent team creates comprehensive docs          │
    │    per feature area - ITERATES until ALL          │
    │    feature areas from Phase 2 are covered)        │
    │                                                   │
    ├───► Check: All features covered? ─── No ─────────┘
    │                  │
    │                 Yes
    ▼                  │
Phase 4: Skill Generation ◄────────────────────────────┘
        (Generate SKILL.md + feature-area-skill-resources/)

IMPORTANT: Phase 3 is iterative. It must loop until ALL feature areas identified in Phase 2's feature-taxonomy.md have corresponding in-depth research. Do not proceed to Phase 4 until every feature area has been investigated.

All phases run strictly sequentially. Each phase depends on the previous phase's output.

Phase 0: Submodule Setup

Option A: Add New Submodule

cd skills/<skill-name>
git submodule add <repo-url> <submodule-name>

Example:

cd skills/azure-data-explorer-kusto-queries
git submodule add https://github.com/MicrosoftDocs/dataexplorer-docs.git dataexplorer-docs

Option B: Discover Existing Submodules

git submodule status

If submodules exist, proceed to Phase 1.

Ask User

If no submodule exists and none was specified:

• Ask user for the documentation repository URL
• Ask user for the target skill name
• Add the submodule

Phase 1: Repository Layout Analysis

Goal: Understand the submodule's structure and produce reference documentation.

Output: investigation-reports/repository-layout/*.md

Agent Team Setup

Create a team for Phase 1:

TeamCreate: "<skill-name>-phase1-repo-layout"

Tasks to Create

1. Directory Structure Analysis

   • Map top-level directories and their purposes
   • Identify documentation vs. code vs. config vs. assets
   • Note any README files and their locations

2. Content Organization Pattern

   • How is content organized? (by feature, by audience, by task?)
   • Identify the navigation/TOC structure
   • Map relationships between sections

3. Key Files Identification

   • Find index files, TOCs, sitemaps
   • Identify schema files, config files
   • Note any templates or examples

Output Format

Create markdown files in investigation-reports/repository-layout/:

• directory-structure.md - Full directory tree with annotations
• content-organization.md - How content is organized, navigation patterns
• key-files.md - Important files and their purposes

Phase 2: Feature Overview Discovery

Goal: Identify all features, sub-features, and feature areas from the documentation.

Output: investigation-reports/feature-overview/*.md

Input: Phase 1 repository layout reports

Agent Team Setup

Create a team for Phase 2:

TeamCreate: "<skill-name>-phase2-feature-discovery"

Tasks to Create

1. Feature Area Identification

   • Read Phase 1 reports to understand repo structure
   • Identify major feature areas/categories
   • Create hierarchical feature taxonomy

2. Sub-Feature Mapping

   • For each feature area, identify sub-features
   • Note feature relationships and dependencies
   • Identify which docs cover which features

3. Feature Prioritization

   • Identify core vs. advanced features
   • Note commonly referenced features
   • Flag features that need deep investigation

Output Format

Create markdown files in investigation-reports/feature-overview/:

• feature-taxonomy.md - Hierarchical list of all features
• feature-to-docs-mapping.md - Which docs cover which features
• priority-features.md - Core features for Phase 3 deep dive

Phase 3: Feature In-Depth Research

Goal: Create comprehensive documentation for EVERY feature area identified in Phase 2.

Output: investigation-reports/feature-in-depth/<feature-area>/*.md

Input: Phase 1 + Phase 2 reports

CRITICAL: Iterate Until Complete

Phase 3 must loop until all feature areas are covered:

1. Read feature-taxonomy.md from Phase 2
2. List ALL feature areas identified
3. Check which feature areas already have in-depth research
4. For each MISSING feature area:
   - Spawn agent team
   - Create reference.md, best-practices.md, examples.md
   - Verify output files exist
5. Repeat steps 3-4 until ALL feature areas have coverage
6. Only then proceed to Phase 4

Do NOT proceed to Phase 4 if any feature areas are missing investigation reports.

Agent Team Setup

Create a team for Phase 3 (may need multiple iterations):

TeamCreate: "<skill-name>-phase3-in-depth"
# or for subsequent iterations:
TeamCreate: "<skill-name>-phase3-in-depth-batch2"

Spawn one agent per feature area identified in Phase 2.

Per-Feature Tasks

For each feature area, create tasks for:

1. Reference Documentation

   • Syntax, parameters, options
   • API signatures, return types
   • Configuration options

2. Best Practices

   • When to use this feature
   • Performance considerations
   • Common patterns and anti-patterns

3. Examples

   • Code samples from the docs
   • Real-world usage scenarios
   • Edge cases and gotchas

Output Format

Create subdirectories in investigation-reports/feature-in-depth/:

feature-in-depth/
├── <feature-area-1>/
│   ├── reference.md
│   ├── best-practices.md
│   └── examples.md
├── <feature-area-2>/
│   └── ...

Phase 4: Skill Generation

Goal: Generate the final skill structure from investigation reports.

Output: SKILL.md + feature-area-skill-resources/

Input: All Phase 1-3 reports

Generate Parent SKILL.md

The parent SKILL.md should include:

1. Frontmatter
   • name: The skill name
   • description: Single-line quoted string with trigger phrases

Use this exact safe pattern:

---
name: <skill-name>
description: "Single-line description with trigger phrases and use conditions."
---

Frontmatter safety rules:

• Always keep description on a single line (no | block scalar, no folded multiline values)
• Always quote description so YAML-special characters (for example :, #, [, ]) are treated as plain text
• Pick a quote style that minimizes escaping:
  • Use double quotes if the text contains apostrophes (')
  • Use single quotes if the text contains many double quotes
• If using double quotes, escape inner double quotes as \"
• If using single quotes, escape apostrophes by doubling them ('')

2. Overview

   • What this skill covers (the product/technology)
   • High-level capabilities

3. Quick Start

   • Most common use cases
   • Basic examples

4. Feature Area Navigation

   • Links to each feature area's resources
   • When to use each feature area

Generate Feature Area Resources

For each feature area, create a subdirectory in feature-area-skill-resources/:

feature-area-skill-resources/
├── <feature-area-1>/
│   ├── overview.md          # From feature-in-depth reference + best practices
│   ├── examples.md          # From feature-in-depth examples
│   └── <sub-feature>.md     # Additional files as needed

Quality Checklist

Before completing Phase 4:

• SKILL.md has proper frontmatter with name and description
• SKILL.md description is a single-line quoted YAML string
• SKILL.md description includes trigger phrases
• All feature areas have corresponding resources
• Cross-references between SKILL.md and feature resources work
• No duplicate content between SKILL.md and resources

Agent Team Coordination

Creating Teams

# Use TeamCreate for each phase
TeamCreate(team_name="<skill-name>-phase<N>-<description>")

Creating Tasks

# Use TaskCreate for work items
TaskCreate(
    subject="<action title>",
    description="<detailed description>",
    activeForm="<present continuous form>"
)

Assigning Work

# Spawn agents and assign to tasks
Task(
    subagent_type="general-purpose",
    team_name="<team-name>",
    name="<agent-name>",
    prompt="<task description>"
)

# Assign task to agent
TaskUpdate(taskId="<id>", owner="<agent-name>")

Phase Transitions

After all tasks in a phase complete:

1. Verify all expected output files exist
2. Send shutdown requests to all phase agents
3. Delete the phase team
4. For Phase 3 ONLY: Check if ALL feature areas from Phase 2 taxonomy are covered
   • If not, create another Phase 3 team and continue
   • Repeat until 100% coverage
5. Create the next phase's team

Phase 3 Completion Checklist

Before proceeding to Phase 4, verify:

# List all feature areas from taxonomy
grep -E "^### [0-9]+\." investigation-reports/feature-overview/feature-taxonomy.md

# List all completed in-depth research
ls investigation-reports/feature-in-depth/

# These two lists must match!

If any feature area is missing from feature-in-depth/, spawn another Phase 3 batch.

Example: ADX Kusto Skill

Phase 0

git submodule add https://github.com/MicrosoftDocs/dataexplorer-docs.git \
    skills/azure-data-explorer-kusto-queries/dataexplorer-docs

Phase 1 Output

investigation-reports/repository-layout/
├── directory-structure.md    # docs/kusto/, docs/azure-data-explorer/, etc.
├── content-organization.md   # Organized by query language, management, ingestion
└── key-files.md              # TOC.yml, index.md locations

Phase 2 Output

investigation-reports/feature-overview/
├── feature-taxonomy.md       # Query language, Operators, Functions, Management...
├── feature-to-docs-mapping.md
└── priority-features.md      # Query language, Operators, Data ingestion

Phase 3 Output (Multiple Iterations)

Phase 3 iterates until ALL 11 feature areas from taxonomy are covered:

Batch 1 (CORE features):

investigation-reports/feature-in-depth/
├── kql-query-language/
├── data-ingestion/
├── visualization-dashboards/
├── time-series-ml/
└── management-commands/

Batch 2 (Remaining features):

investigation-reports/feature-in-depth/
├── ... (batch 1)
├── api-sdk-integration/
├── security-access-control/
├── cluster-management/
├── business-continuity/
├── integration-services/
├── udf-functions-library/
└── tools-clients/

Verification before Phase 4:

• Taxonomy lists 11 feature areas
• feature-in-depth/ has 11 subdirectories
• ✅ 100% coverage achieved → proceed to Phase 4

Phase 4 Output

skills/azure-data-explorer-kusto-queries/
├── SKILL.md                  # Parent skill for ADX Kusto
├── feature-area-skill-resources/
│   ├── kql-query-language/
│   ├── data-ingestion/
│   ├── visualization-dashboards/
│   ├── time-series-ml/
│   ├── management-commands/
│   ├── api-sdk-integration/
│   ├── security-access-control/
│   ├── cluster-management/
│   ├── business-continuity/
│   ├── integration-services/
│   ├── udf-functions-library/
│   └── tools-clients/        # ALL 11+ feature areas covered
├── investigation-reports/    # Preserved for reference
└── dataexplorer-docs/        # Submodule

See Also

• skill-creator skill - For general skill creation guidance
• TeamCreate, TaskCreate, TaskUpdate, SendMessage - Agent coordination tools