Phenomenai

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns specific data (state, verdict, etc.) and requires an issue number from 'propose_term,' which adds useful context. However, it lacks details on error handling, authentication needs, or rate limits, which are important for a tool interacting with external systems like GitHub.

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 front-loaded with the core purpose, followed by return details and usage guidance, all in three concise sentences. Every sentence adds value without redundancy, making it easy to scan and understand quickly.

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 has an output schema, the description doesn't need to detail return values. It covers the purpose, usage, and parameter semantics well. However, as a tool with no annotations and external dependencies (GitHub), it could benefit from mentioning potential errors or prerequisites, slightly reducing 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 description coverage is 0%, so the description must compensate. It explains the single parameter 'issue_number' by specifying it's 'The GitHub issue number returned by propose_term,' adding meaningful context beyond the schema's basic type. This clarifies the parameter's origin and purpose, though it could note format constraints (e.g., positive integer).

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 with a specific verb ('check') and resource ('review status of a proposed term'), and distinguishes it from its sibling 'propose_term' by indicating it's for follow-up. It explicitly mentions what information is returned (state, verdict, scores, feedback), making the purpose unambiguous.

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 provides explicit guidance on when to use this tool: 'to follow up on proposals submitted via `propose_term`.' It names the specific alternative ('propose_term') and clarifies the context (community-submission issues), leaving no ambiguity about its intended use case.

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