vision.query

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

The description lacks behavioral details beyond the brief statement. It does not disclose whether the tool is read-only, what side effects occur, or any constraints like requiring a specific capture state. With no annotations, the description carries the full burden but fails to provide this context.

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 extremely concise (10 words) but lacks necessary structure and detail. It is under-specified, missing parameter explanations and usage context, which reduces its effectiveness.

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 complexity (3 required params, nested object in 'query', no schema descriptions, no annotations), the description is incomplete. It does not explain how to construct the query object, what capture_id and project_path refer to, or what the output contains, making it inadequate for an AI agent.

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 0%, meaning the input schema provides no parameter descriptions. The tool description adds no meaning to parameters like 'query', 'capture_id', or 'project_path'—it does not explain their roles, formats, or constraints.

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's purpose: 'Query an observed perceptual graph with exact artifact citation.' It uses a specific verb and resource, and mentioning 'exact artifact citation' differentiates it from siblings like vision.observe or vision.explain_region.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions, which is insufficient for an AI agent to decide when to invoke this tool.

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