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CSOAI-ORG

vector-knowledge-graph-mcp

semantic_node_search

Search your knowledge graph for nodes that best match the semantic meaning of a given query using vector embeddings.

Instructions

Search for nodes using semantic similarity matching against stored embeddings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It mentions semantic matching but fails to disclose prerequisites (e.g., embeddings must exist), required permissions, or behavior in edge cases like no matches. The api_key parameter is mentioned in schema but not explained in description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with key verb and resource. Appropriate length for the information provided, though lacks detail in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists, so return format is covered, but the description omits critical context: how api_key is used, what top_k controls, what query format to use, and preconditions. With 3 parameters and no annotations, the description is insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no information about the three parameters (query, top_k, api_key). Their semantics are entirely dependent on schema titles and defaults, which are minimal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (Search), resource (nodes), and method (semantic similarity matching against stored embeddings), which distinguishes it from sibling tools like add_edge or trace_compliance_chain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives, or when not to use it. The description is just a single statement of function without context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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