Check whether a specific claim matches an entity's business-supplied record on AITWIRE. Returns verified / contradicted / unknown with a confidence score, so you can attribute the result.
| Name | Required | Description | Default |
|---|---|---|---|
| claim | Yes | Claim to verify | |
| entity | Yes | Entity domain or name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive. Description adds value by detailing return outcomes (verified/contradicted/unknown) and confidence score, and mentions attribution of results.
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 are concise and front-loaded, conveying purpose and output without unnecessary words.
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?
Without an output schema, the description compensates by specifying return types and confidence score, which is sufficient for a simple tool with two parameters.
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 provides descriptions for both parameters (100% coverage). The description does not add any additional meaning beyond what the schema already states.
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 checks a claim against an entity's record on AITWIRE, specifying it returns verified/contradicted/unknown with confidence score. It distinguishes from siblings (entity feeds and lookup) by focusing on verification.
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?
Implied usage for verifying claims against a business record, but no explicit guidance on when to use this tool vs. siblings, nor when not to use it.
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.