A
licenseNot graded
qualityA
maintenanceProvides a traversable knowledge graph of the NVIDIA NemoClaw stack, enabling deterministic queries over its architecture, dependencies, and policies via MCP.
2
MIT
ckg-nvidia-ai
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TDQS
A3.7/5.0
Scored across 8 tools
Disambiguation4/5
Tools are mostly distinct: list_domains vs list_ecosystem differ in scope, ask_nvidia vs route_query differ in output, and verify_source is unique. However, search_concepts, query_ckg, and get_prerequisites all involve graph exploration and could cause some initial ambiguity, though the descriptions clarify their specific roles.
Naming Consistency4/5
Most tool names follow a verb_noun snake_case pattern (list_domains, search_concepts, get_prerequisites, route_query, verify_source). query_ckg and ask_nvidia deviate slightly with acronyms/proper nouns, but the overall verb-first style remains consistent and predictable.
Tool Count5/5
The 8 tools form a focused set for exploring an NVIDIA AI knowledge graph: domain listing, concept search, traversal, prerequisite chains, natural language QA, routing, ecosystem discovery, and source verification. This is neither sparse nor bloated for the stated purpose.
Completeness4/5
The toolset covers the main read-only knowledge graph workflows: discovery, search, traversal, prerequisite chains, question answering, routing, and provenance verification. A minor gap is the absence of a direct 'get concept details' tool, but query_ckg and search_concepts can cover that need.
Maintenance
ActivityStale
ResponsivenessNo issues