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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the resolution purpose and the submit_request linkage, but says nothing about matching behavior (partial/fuzzy matching), whether multiple candidates can be returned, or what happens on no match — meaningful gaps for a lookup tool that agents will often chain into submit_request.

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 sentences, front-loaded with the core action and followed by the concrete use case. The long em-dash enumeration of entity types is slightly listy but is doing real work by scoping what can be searched.

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?

There is no output schema, so the description carries the burden of describing the return value; it implies an id but does not say whether a list of candidates or a single match comes back, nor how ambiguity is surfaced. It is adequate for a 3-parameter lookup, but the return shape is left for the agent to discover.

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 each parameter is already documented, including the empty-query count behavior and the workflow_id scoping rationale. The description adds little parameter-level meaning beyond reinforcing that query holds a user's spoken name and that entity_type spans the eight listed types. Baseline 3 is appropriate when the schema does the heavy lifting.

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+resource: 'Resolve a name to an id' for reference data, then enumerates the entity kinds (vendors, customers, departments, locations, cost centers, categories, taxes, products). This clearly separates it from siblings like search_team_users or list_workflows, and the 'id that submit_request expects' phrasing pins down its role in the flow.

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?

'Call this to turn a user's words (\'Acme\', \'Marketing\') into the id that submit_request expects' gives an explicit trigger and names the downstream tool it feeds. It stops short of stating when NOT to use it (e.g., team members go to search_team_users) or what to do when multiple matches come back, so it is clear context without full exclusions.

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