Metis — List Research Entities

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

With no annotations, the description carries full burden. It discloses that it lists entities with claim count and last update, which is appropriate for a read-only list operation. However, it does not mention potential traits like pagination, performance, or safety, but given the simplicity of the tool, it is still transparent.

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 two sentences long, with no waste. The first sentence states the core functionality, and the second provides usage guidance. It is front-loaded and efficient.

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 simplicity (0 params, output schema exists), the description provides enough context: what it lists (entities, claim count, last update) and how it fits into a workflow (overview before drilling). No additional information is needed.

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 input schema has zero parameters, so schema coverage is 100%. The description does not add parameter info because none exist. According to guidelines, 0 parameters yields a baseline of 4, which is appropriate.

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 specifies the verb 'list', the resource 'entities in the research timeline', and the included fields 'claim count and last update'. It clearly distinguishes itself from the sibling tool 'query_research_timeline' by positioning as an overview tool before drilling into specifics.

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?

Explicitly states when to use: 'Use this to get an overview of what topics have tracked beliefs, before drilling into a specific entity with query_research_timeline()'. It names an alternative and implies when not to use (when you need detail on a specific entity).

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