tigergraph__fetch_vector

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

Annotations already establish readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds the GSQL implementation detail and the REST limitation, but discloses little beyond that about return shape, auth, or edge cases.

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?

Two short sentences, with the action front-loaded and the caveat placed second. No filler or repetition of schema content.

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?

For a read-only fetch with 100% schema coverage and only two required parameters, the description plus annotations are largely sufficient for an agent to call the tool. The main missing piece is a description of the return shape, especially since the tool has no output schema, so a 4 rather than 5.

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?

Schema description coverage is 100%, so all five parameters have individual descriptions in the schema. The tool description itself adds no parameter-specific meaning beyond the general 'vector data' context, justifying the baseline score.

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?

Description opens with a specific verb and resource ('Fetch vertices with their vector data') and names the underlying mechanism ('GSQL PRINT WITH VECTOR'), which distinguishes this from REST-based vertex retrieval siblings such as get_nodes. The scope is clear and actionable.

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 note that 'Vector attributes cannot be fetched via REST API' gives a clear reason to choose this GSQL-backed tool over REST-based alternatives. It does not explicitly name sibling tools or state 'use X when not Y,' so the guidance is context rather than an explicit routing rule.

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