AITWIRE

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

Annotations (readOnlyHint, destructiveHint) are already present. The description adds context about the feed types and the source of tenant_id, enhancing transparency beyond 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?

The description is a single sentence with a parenthetical, front-loading verb and resource. No wasted words; every element serves a purpose.

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 no output schema, the description adequately explains input and context. However, it does not mention return format or pagination details beyond 'page', leaving minor gaps.

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 description adds meaning by listing feed_type options and clarifying that tenant_id comes from aitwire_entity_lookup. Schema coverage is high (67%), and the description compensates for the remaining gaps.

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 uses a specific verb ('page') and clearly identifies the resource ('entity's structured feeds'). It lists the feed types (products, services, etc.) and distinguishes from siblings by referencing aitwire_entity_lookup for tenant_id.

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 implies the tool is used to retrieve an entity's feeds after obtaining a tenant_id from aitwire_entity_lookup. It does not explicitly state when not to use or alternatives, but the dependency is clear.

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

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

Annotations already indicate the tool is read-only and non-destructive. The description adds behavioral context by detailing the returned data (confirmed description, feed URLs, proof counts with confirmation dates) and the constraint that only entities that have published to AITWIRE will return results. This goes beyond the annotations to provide useful behavioral expectations.

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 two sentences long, no redundancy, and directly states the core functionality and return information. It is front-loaded with the verb and resource, making it easy for an AI agent to parse 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?

Despite having no output schema, the description sufficiently explains what the tool returns (confirmed description, feed URLs, proof counts with dates) and a key behavior (no match for non-published entities). For a simple lookup tool with clear input parameters, this is nearly complete. One might argue that it could explicitly state that both parameters are optional and at least one must be provided, but the context signals indicate zero required parameters, so that detail is implicitly available.

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 input schema has 100% coverage with clear descriptions for both parameters ('name' and 'domain'), so the schema already conveys their meaning. The description adds that either parameter can be used, but does not specify that at least one is required (though it's implied). Overall, the description adds minimal semantic value beyond the schema, placing it at the baseline.

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: looking up a business-supplied entity record by domain or name on AITWIRE. It specifies the types of entities (business, brand, organization, person, website) and the returned fields (confirmed description, feed URLs, proof counts with dates). This distinguishes it from sibling tools like aitwire_entity_feeds and aitwire_grounding, which handle related but different functionality.

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 clear context on when to use the tool: to retrieve an entity's record by providing a domain or name. It also states the outcome when no match is found (returns no match for entities not published to AITWIRE). However, it does not explicitly compare with sibling tools or provide when-not-to-use guidelines, so it is slightly less than perfect.

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

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

Annotations already mark readOnlyHint=true; description adds that it returns verified/contradicted/unknown with confidence score. 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 focused sentences, no extraneous content. Verb and resource are front-loaded.

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 simple two-parameter read-only tool with no output schema, the description fully explains behavior and return value. No gaps.

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 covers both parameters with descriptions; the tool description restates their purpose but adds no new semantic detail beyond what is in the schema.

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?

Clearly states the tool checks a claim against an entity's record on AITWIRE. Distinct from siblings (entity_feeds, entity_lookup) which handle different operations.

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?

Implies usage for verifying claims but provides no explicit guidance on when not to use it or alternatives. With siblings present, exclusion criteria would be helpful.

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