Add OpenClaw Skills: graph_query, compare_pipelines, extract_entities, benchmark, cost_estimate, explore_graph"

openclaw/skills/graph_query/SKILL.md

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+# graph_query
+
+Query the TigerGraph knowledge graph using natural language. Performs dual-level keyword extraction, entity vector search, and multi-hop graph traversal to find relevant entities, relationships, and evidence passages.
+
+## Parameters
+- `query` (string, required): Natural language question to search the knowledge graph
+- `depth` (integer, optional, default=2): Number of hops for graph traversal (1-4)
+- `top_k` (integer, optional, default=5): Number of seed entities to retrieve
+
+## Returns
+JSON object with:
+- `entities`: List of entities found with names, types, and descriptions
+- `relations`: List of relationships traversed with source, target, and type
+- `passages`: Relevant text chunks connected to discovered entities
+- `reasoning_path`: Step-by-step explanation of the graph traversal
+
+## Example
+```
+graph_query "Were Scott Derrickson and Ed Wood of the same nationality?" --depth 2
+```
+
+## Notes
+- Requires TigerGraph connection (set TG_HOST, TG_PASSWORD env vars)
+- Falls back to in-memory entity extraction if TigerGraph unavailable
+- Uses the configured LLM provider for keyword extraction