
docs-guide
by Nubaeon
Cognitive Operating System for AI Agents - Git-native epistemic middleware enabling self-awareness, multi-agent coordination, and measurable learning through CASCADE workflow. Turns context loss into transparent uncertainty tracking.
SKILL.md
name: docs-guide description: Interactive documentation guide - helps users explore and understand project documentation. Use when user asks about features, APIs, configuration, or wants to learn how something works. Retrieves focused docs and guides through them interactively. allowed-tools: Bash(empirica docs-explain:),Bash(python -m docpistemic.cli explain:),Read,Glob,Grep
Interactive Documentation Guide
Overview
This skill helps users explore project documentation interactively. It retrieves relevant documentation sections and guides users through understanding them, with follow-up suggestions.
When to Use
- User asks "how do I...?" or "what is...?"
- User wants to understand a feature, API, or concept
- User is exploring the codebase and needs guidance
- User asks about configuration, installation, or usage
Workflow
1. Understand the Query
First, identify:
- Topic: General subject area (auth, api, config, install, etc.)
- Question: Specific question if provided
- Audience: developer, user, or ai-agent context
2. Retrieve Documentation
For Empirica project:
empirica docs-explain --topic "<topic>" --output json
# or
empirica docs-explain --question "<question>" --output json
For external projects (using docpistemic):
python -m docpistemic.cli explain /path/to/project --topic "<topic>" --output json
3. Present Results Interactively
After retrieving docs, guide the user:
- Summarize - Brief overview of what was found
- Key Points - Extract the most relevant 2-3 points
- Code Examples - Show relevant code snippets if available
- Related Topics - Suggest follow-up areas to explore
- Ask - Check if they want more detail on any aspect
4. Follow-up Guidance
Based on the retrieved related_topics, offer to:
- Dive deeper into a specific section
- Show related commands or APIs
- Explain concepts mentioned in the docs
- Find code examples in the actual codebase
Example Interaction
User: "How do sessions work in Empirica?"
Response pattern:
- Run:
empirica docs-explain --topic "sessions" --output json - Present: "Sessions in Empirica track AI agent work context..."
- Key points from docs
- Relevant CLI commands mentioned
- "Would you like me to explain session-create, or show how sessions relate to goals?"
Topic Aliases
Common topics map to multiple keywords:
- auth → authentication, login, oauth, jwt, token
- api → endpoints, routes, rest, graphql
- config → configuration, settings, environment
- install → installation, setup, quickstart
- test → testing, pytest, coverage
- session → sessions, context, bootstrap
Interactive Patterns
For "How do I...?" questions
- Search for the action/verb in question
- Find relevant command or API
- Show usage example
- Offer to show more examples or related commands
For "What is...?" questions
- Search for concept definition
- Explain in context of the project
- Show where it's used
- Suggest related concepts
For troubleshooting
- Search for error or symptom
- Find relevant documentation
- Suggest diagnostic commands
- Offer to search codebase if docs don't help
Output Format
When presenting results, use clear structure:
## [Topic/Question]
**Summary:** Brief overview of what was found
**Key Points:**
- Point 1 with source reference
- Point 2 with source reference
**Relevant Commands:**
- `command` - description
**See Also:** [related topics]
**Want to explore:** [specific follow-ups]?
Notes
- Always cite source files from the docs
- If docs are sparse, offer to search codebase directly
- Suggest running commands with
--helpfor detailed usage - For complex topics, break into multiple exchanges
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
1ヶ月以内に更新
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
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