memcp_related

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

With no annotations provided, the description carries full burden. It describes the traversal operation and edge types but omits specific behavioral details like whether the tool is read-only, error handling for missing insight_id, or performance characteristics.

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

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

The description is concise with a front-loaded lead sentence, followed by a brief explanation of what the tool does, then parameter details. No extraneous information.

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

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

Given the tool's graph traversal complexity and an existing output schema, the description adequately covers the main behavior. However, it could mention the expected output format or common error conditions for completeness.

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

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

The schema coverage is 0%, but the Arg descriptions add meaning: insight_id is the start point, edge_type filters by type (with allowed values listed), and depth specifies hops. This compensates for the schema's lack of property descriptions.

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

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

The description clearly states the tool traverses a graph from an insight to find connected knowledge, specifying relationship types like semantic similarity, temporal proximity, causal chains, or shared entities. This distinguishes it from sibling tools like memcp_search and memcp_recall.

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

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

The description implies usage when wanting to explore graph connections from a given insight, but lacks explicit guidance on when to use this tool versus alternatives like memcp_search or memcp_peek_chunk, and does not provide exclusions.

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