| name | lookup-lc-doc |
| description | Search and retrieve LimaCharlie documentation from GitHub repositories. Use when users ask about LimaCharlie platform features, SDKs, APIs, D&R rules, LCQL, sensors, outputs, extensions, integrations, AI skills, agents, or any LimaCharlie-related topics. |
Looking Up LimaCharlie Documentation
Use this skill proactively whenever a user asks about LimaCharlie features, configuration, or implementation.
When to Use
Invoke this skill when users ask about:
- Platform features: D&R rules, LCQL queries, sensors, events, outputs, extensions
- APIs: REST API usage, authentication, endpoints
- SDKs: Python SDK or Go SDK usage, examples, methods
- Configuration: Setting up integrations, adapters, outputs
- Getting started: Tutorials, quick start guides, installation
- AI capabilities: Skills, agents, commands available in LimaCharlie AI
- Any LimaCharlie topic: General questions about capabilities or how to use features
Documentation Sources
Documentation is fetched from two GitHub repositories using WebFetch:
| Repository | Base URL |
|---|---|
| Platform docs | https://raw.githubusercontent.com/refractionPOINT/documentation/master/ |
| AI skills/agents | https://raw.githubusercontent.com/refractionPOINT/lc-ai/master/ |
How to Use - DYNAMIC DISCOVERY
Step 1: Discover Available Content
ALWAYS start by fetching index/navigation files to discover the current structure:
# For platform documentation - fetch the main index
WebFetch: https://raw.githubusercontent.com/refractionPOINT/documentation/master/docs/index.md
# For AI skills/agents - fetch the summary files
WebFetch: https://raw.githubusercontent.com/refractionPOINT/lc-ai/master/marketplace/plugins/lc-essentials/README.md
WebFetch: https://raw.githubusercontent.com/refractionPOINT/lc-ai/master/marketplace/plugins/lc-essentials/SKILLS_SUMMARY.md
These index files contain links to all available documentation. Parse the links to discover:
- Available categories and sections
- File paths for specific topics
- Related documentation that may be relevant
Step 2: Follow Links from Index Files
After fetching index files, extract the file paths from links in the markdown content:
- Links appear as
[text](path/to/file.md)or[:icon: text](path/to/file.md) - Construct full URLs by combining base URL + path
- Identify which links are relevant to the user's question
Step 3: Fetch Relevant Documentation
Based on what you discovered in the index files, fetch the specific documentation:
# Construct URLs dynamically from discovered paths
WebFetch: {base_url}/{discovered_path}
Fetch multiple relevant files in parallel - don't stop at one file.
Step 4: Provide Comprehensive Response
- Include information from all files fetched
- Organize content logically (overview -> details -> examples)
- Mention which documentation sources the information came from
- If the answer spans multiple topics, include all relevant documentation
Example Workflow
User: "How do I write D&R rules?"
1. Discover structure:
WebFetch: https://raw.githubusercontent.com/refractionPOINT/documentation/master/docs/index.md
-> Parse the markdown to find links related to "Detection", "Response", "D&R", "rules"
-> Discover paths like: limacharlie/doc/Detection_and_Response/detection-and-response-rules.md
2. Fetch discovered docs (in parallel):
WebFetch: https://raw.githubusercontent.com/refractionPOINT/documentation/master/docs/{discovered_path_1}
WebFetch: https://raw.githubusercontent.com/refractionPOINT/documentation/master/docs/{discovered_path_2}
(paths extracted from index file links)
3. Respond with comprehensive answer combining all sources
Key Principles
- Dynamic discovery: NEVER hardcode file paths - always discover them from index files
- Use WebFetch: All documentation is fetched via raw.githubusercontent.com URLs
- Parse links: Extract file paths from markdown links in index/summary files
- Be thorough: Fetch multiple relevant files, not just one
- Parallel fetches: Use multiple WebFetch calls in parallel for efficiency
- Combine sources: Information may span both repositories