Build and query an evidence-lined GEO knowledge graph from approved source bundles. Use for entity normalization, relation lineage, conflicting fact preservation, incremental source-hash updates, local/global knowledge queries, 知识图谱, 知识库, and 知识治理. Exclude unsourced facts, hidden conflict resolution, autonomous crawling, and external database mutation.
Resources
6Install
npx skillscat add yaojingang/geohub/geo-knowledge Install via the SkillsCat registry.
GEO Knowledge
Workflow
- Read
references/knowledge-method.mdand prepare approved source bundles with stable IDs and SHA-256 hashes. - Run
python3 scripts/run_knowledge.py --input <request.json> --output <runs-root>. - Inspect canonical identities, aliases, relation source IDs, validity dates, source coverage, conflicts, and gaps.
- Use the local query for an entity neighborhood or the global query for communities, coverage, conflicts, and gaps.
- For incremental updates, replace only source bundles whose hashes changed and rebuild the governed graph.
Output contract
Produce the input snapshot, knowledge-graph.json, query result, evidence ledger, quality report, lineage, and manifest. Read references/output-contract.md before reuse.
Boundaries
Execution stays offline and file-backed. Conflicting approved facts remain visible for human review. The Skill never crawls, logs in, mutates an external knowledge base, or silently selects one conflicting value.