skills/deep-knowledge-skill-creator/SKILL.md
Multi-phase workflow for converting documentation repositories into comprehensive skills; use when creating or refreshing skills from docs/codebases, investigating large repos systematically, or turning submodule knowledge into investigation reports plus generated skill content.
npx skillsauth add johnsonshi/skills365 deep-knowledge-skill-creatorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Convert documentation repositories into comprehensive, well-structured skills through systematic multi-phase investigation using agent teams.
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
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.
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
git submodule status
If submodules exist, proceed to Phase 1.
If no submodule exists and none was specified:
Goal: Understand the submodule's structure and produce reference documentation.
Output: investigation-reports/repository-layout/*.md
Create a team for Phase 1:
TeamCreate: "<skill-name>-phase1-repo-layout"
Directory Structure Analysis
Content Organization Pattern
Key Files Identification
Create markdown files in investigation-reports/repository-layout/:
directory-structure.md - Full directory tree with annotationscontent-organization.md - How content is organized, navigation patternskey-files.md - Important files and their purposesGoal: Identify all features, sub-features, and feature areas from the documentation.
Output: investigation-reports/feature-overview/*.md
Input: Phase 1 repository layout reports
Create a team for Phase 2:
TeamCreate: "<skill-name>-phase2-feature-discovery"
Feature Area Identification
Sub-Feature Mapping
Feature Prioritization
Create markdown files in investigation-reports/feature-overview/:
feature-taxonomy.md - Hierarchical list of all featuresfeature-to-docs-mapping.md - Which docs cover which featurespriority-features.md - Core features for Phase 3 deep diveGoal: 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
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.
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.
For each feature area, create tasks for:
Reference Documentation
Best Practices
Examples
Create subdirectories in investigation-reports/feature-in-depth/:
feature-in-depth/
├── <feature-area-1>/
│ ├── reference.md
│ ├── best-practices.md
│ └── examples.md
├── <feature-area-2>/
│ └── ...
Goal: Generate the final skill structure from investigation reports.
Output: SKILL.md + feature-area-skill-resources/
Input: All Phase 1-3 reports
The parent SKILL.md should include:
name: The skill namedescription: Single-line quoted string with trigger phrasesUse this exact safe pattern:
---
name: <skill-name>
description: "Single-line description with trigger phrases and use conditions."
---
Frontmatter safety rules:
description on a single line (no | block scalar, no folded multiline values)description so YAML-special characters (for example :, #, [, ]) are treated as plain text')\"'')Overview
Quick Start
Feature Area Navigation
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
Before completing Phase 4:
description is a single-line quoted YAML string# Use TeamCreate for each phase
TeamCreate(team_name="<skill-name>-phase<N>-<description>")
# Use TaskCreate for work items
TaskCreate(
subject="<action title>",
description="<detailed description>",
activeForm="<present continuous form>"
)
# 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>")
After all tasks in a phase complete:
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.
git submodule add https://github.com/MicrosoftDocs/dataexplorer-docs.git \
skills/azure-data-explorer-kusto-queries/dataexplorer-docs
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
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 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:
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
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Comprehensive guide for Azure Data Explorer (ADX) and Kusto Query Language (KQL); use when writing/optimizing KQL queries, setting up ingestion, building dashboards, doing time-series/ML analysis, configuring management/security, or when users mention Kusto, KQL, ADX, Azure Data Explorer, or log analytics queries.
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