Claude-skill-registry kg-insights
Helps users discover patterns and insights in their Knowledge Graphs.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/kg-insights" ~/.claude/skills/majiayu000-claude-skill-registry-kg-insights && rm -rf "$T"
skills/data/kg-insights/SKILL.mdKnowledge Graph Insights
Help users explore their Knowledge Graph with natural questions. Transform graph analysis into actionable insights with clear explanations of why each finding matters.
What Users Can Ask
| Question | Sub-Resource | When to Use |
|---|---|---|
| "Who are the key players?" | | User wants to find important entities |
| "How is X connected to Y?" | | User wants to understand relationship paths |
| "What groups or clusters exist?" | | User wants to see topic organization |
| "Where is X mentioned?" | | User wants source citations for claims |
| "What can I do with this graph?" | | User is unsure what's possible |
Proactive Triggers
Invoke this skill automatically in these situations:
After Extraction Completes
When
extract_to_kg finishes successfully:
Great! I've added [N] entities and [M] relationships to your graph. Your Knowledge Graph now has [total] entities. Would you like me to: 1. Show who the key players are 2. Find interesting connections 3. See how topics cluster together Just ask, or type a number!
After Milestone Reached
When graph reaches 50+ entities:
Your Knowledge Graph is growing! With [N] entities, there's a lot to explore. Some questions you might find interesting: - "Who appears most often across my sources?" - "How is [popular entity] connected to [another]?" - "What are the main topic clusters?"
When User Seems Unsure
If user asks vague questions like "what now?" or "what's next?":
- Read
for smart suggestionsPOWER-QUERY.md - Present personalized options based on their graph's content
Tool Mapping
Map natural questions to KG tools:
| User Intent | Tool | Parameters |
|---|---|---|
| Key players | | |
| Connections | Graph path query | source/target labels |
| Evidence | Source lookup | entity/relationship ID |
| Statistics | | |
Response Format
Always Include
- Direct Answer - Lead with the key finding
- Supporting Data - Table or list with specifics
- Why This Matters - Explain the significance
- Explore Further - 2-3 follow-up suggestions
Example Response Structure
## Key Players in Your Graph Based on connection analysis, here are the most influential entities: | Entity | Type | Connections | Appears In | |--------|------|-------------|------------| | [Name] | Person | 12 | 4 sources | | [Name] | Organization | 8 | 3 sources | ### Why This Matters These entities are central to your research because: - **[Name]** appears across multiple sources, suggesting they're a recurring theme - **[Name]** connects to many other entities, making them a good entry point ### Explore Further - "How is [Name A] connected to [Name B]?" — Trace the relationship path - "Show me [Name]'s connections" — See their full network - "What sources mention [Name]?" — Find evidence and citations
Follow-Up Format (CRITICAL - MUST READ)
The frontend parses your "Explore Further" section and creates clickable suggestion cards.
For this to work, you MUST use this exact format:
### Explore Further - "Query in quotes" — Brief description - "Another query" — Brief description
Required Elements:
- Use a bullet list (
or-
)* - Put the query in double quotes (
)"query here" - Add a description after em-dash (
) or colon (—
):
Correct:
- "Show me Fear's connections" — See the full network - "How is Hope connected to Fear?" — Trace the path
Wrong (cards won't appear):
- Show me Fear's connections - How is Hope connected to Fear?
Replace placeholders like
[Name] with actual entity names from the user's graph.
Graph Analysis Methods
Use these approaches when answering questions:
Finding Key Players (Degree Centrality)
Count connections for each entity. More connections = more central.
- Use
for type breakdownget_kg_stats - Cross-reference with source counts
Finding Paths (Shortest Path)
Use NetworkX path finding to show how entities connect.
- Show step-by-step: A -> B -> C
- Include relationship types at each step
Finding Clusters (Community Detection)
Group entities that are densely connected.
- Use entity types as initial groupings
- Look for entities bridging groups
Finding Evidence (Provenance)
Trace entities and relationships back to sources.
- Include confidence scores
- Quote relevant text when available
Critical Rules
- Plain Language First - Say "well-connected" not "high degree centrality"
- Always Explain Why - Every insight needs a "why this matters"
- Offer Next Steps - Never leave users without options
- Use Real Data - Never make up entity names or statistics
- Cite Sources - When showing evidence, include source references
- Quote Follow-Ups - ALWAYS put follow-up queries in "double quotes" with descriptions
- Use Entity Names - Replace [placeholders] with actual names from the user's graph
Error Handling
| Issue | Response |
|---|---|
| No project selected | "Please select a Knowledge Graph project first, or create one with " |
| Empty graph | "Your graph doesn't have any entities yet. Add a transcript with " |
| Entity not found | "I couldn't find '[name]' in your graph. Try a different spelling or check available entities" |
| No path exists | "These entities aren't connected in your graph. They may appear in separate contexts" |