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

Annotations already declare readOnly/idempotent/non-destructive (and closed-world), so the safety profile is covered. The description adds real behavioral context beyond them — that the result carries a confidence and an ambiguity flag, and that a ranked `alternatives` list comes back — which helps the agent interpret output.

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?

Dense but front-loaded: the core purpose leads, then a single sentence covers inputs and one covers output/resumption. It is slightly long with parenthetical examples, but no sentence is redundant.

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 4-param, output-schema-backed lookup tool, everything needed to call it correctly is present: required vs optional params, their interaction, and the downstream handoff to `fetch`. Return-value detail is a bonus rather than a necessity.

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 coverage is 100%, so the baseline is 3. The description earns above baseline by giving concrete examples ('Mercury', `context`: "planet orbit") and by clarifying that `type` uses the same topic id that `fetch` names as `topic:…`, cross-linking the two params' semantics.

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?

States a specific verb and resource — resolving a name to an Edgepedia article — and immediately differentiates itself from siblings by framing the task as disambiguation (best match, confidence, ambiguity, alternatives). An agent can tell this apart from `search`, `fetch`, `connect`, or `related` without opening any schema.

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?

Gives clear usage context: pass a name from a text, optionally with surrounding words or a topic id, and it routes downstream by saying 'pass an id to `fetch`'. It does not explicitly contrast with the sibling `search`, so the when-not-to-use case is left implicit.

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