Look up a business, brand, organization, person, or website's business-supplied entity record on AITWIRE by domain or name — its confirmed description, feed URLs, and proof counts, each carrying the date it was confirmed. Returns no match for entities that have not published to AITWIRE.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Entity name (e.g. 'AITWIRE') | |
| domain | No | Domain (e.g. 'example.com') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds value by disclosing that unmatched entities return no result and that results include confirmation dates. No contradictions with annotations.
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 with no fluff. Every sentence provides essential information: what the tool does, how to use it, and what to expect.
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 of the tool (2 optional parameters, no output schema), the description covers the returned fields and an important edge case (no match). Could mention behavior when both parameters are provided, but not necessary.
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 100%, so baseline is 3. Description does not add extra meaning beyond the schema's parameter descriptions.
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?
Description clearly specifies the verb 'look up', the target resource ('entity record on AITWIRE'), and the types of entities (business, brand, etc.). It differentiates from siblings by focusing on business-supplied records with confirmation dates.
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?
Description implies usage for basic entity lookup but does not explicitly differentiate from sibling tools like aitwire_entity_feeds or aitwire_grounding. It mentions that lookup is by domain or name and that only published entities are returned, providing context but no alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: entity_lookup retrieves an entity record, entity_feeds pages structured content for that entity, and grounding checks a claim against the entity's record. No overlap or ambiguity.
All tool names start with 'aitwire_' and use snake_case, but two include 'entity_' and one does not (aitwire_grounding). Minor inconsistency but still predictable and readable.
With only 3 tools, the server is tightly scoped to entity verification and feed retrieval. Each tool is essential, and the count is ideal for this focused domain.
The tool surface covers the full workflow: lookup an entity, retrieve its feeds, and ground claims against its record. No obvious gaps for the stated purpose of verifying entity-supplied information.