directory

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

With no annotations, the description carries the full burden. It explains that the agent uses live data (not scraped HTML) and the business's own knowledge base. However, it omits any discussion of authentication, rate limits, or side effects, which are typical for such a tool.

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: the first states the core action and method, the second provides the source for the slug parameter. No extraneous information.

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?

The tool has no output schema, and the description does not specify the format of the answer (e.g., plain text, JSON). However, the mention that 'the agent answers' is likely sufficient for an AI agent. Slightly incomplete but acceptable.

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% with descriptions for both parameters (slug example and question). The description adds value by mentioning the slug source but does not deepen understanding beyond the schema. Baseline 3 is appropriate.

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 action ('Ask'), the resource ('a specific business's ANOTS agent'), and the method ('by slug'). It also distinguishes from sibling tools by explaining where to get the slug and contrasting with 'scraped HTML'.

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 a clear prerequisite ('Get the slug from search_businesses') and the context of using it for a specific business. However, it lacks explicit when-not to use or alternatives (e.g., find_and_ask for broader queries).

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?

No annotations are provided, so the description must disclose behavioral traits. It states the tool returns answers side by side and accepts a query and limit. However, it does not explicitly say whether the operation is read-only, nor does it disclose any potential side effects, rate limits, or authentication needs. For a query tool, this is minimally adequate but lacks full transparency.

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 that are front-loaded with the core action. No wasted words; every sentence adds value. Efficient and clear.

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 tool with two parameters and no output schema, the description is largely complete. It explains the combined functionality and hints at the return format ('answers side by side'). It could mention that it searches across the directory, but overall sufficient.

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 the description does not need to add much. The description adds no new meaning beyond the schema: it describes the query as 'the need or question to route' and limit as 'how many businesses to ask', which mirrors the schema descriptions. Baseline 3 is appropriate.

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 verb 'Discover and ask' and the resource 'ANOTS businesses', indicating a combined search-and-ask operation. It distinguishes itself from siblings by highlighting the single-step combined action.

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 specifies when to use: for 'purchase-intent or research question across the directory'. It implies that for asking a specific business, one would use 'ask_business' instead, and for just searching, 'search_businesses'. However, it does not explicitly state when not to use.

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?

With no annotations, the description carries full burden. It mentions returning matching businesses, implying read-only behavior, but doesn't discuss auth, rate limits, or other behaviors. Adequate for a simple search tool.

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 redundancy. Purpose and return values 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 basic search tool with two parameters and no output schema, the description covers purpose, returns, and usage sequence. Could add pagination details 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 coverage is 100%, so the description adds no new meaning beyond the schema. The description reinforces the purpose but doesn't enrich parameter understanding.

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 searches a directory and returns specific fields (slug, name, etc.). It distinguishes itself from siblings like 'ask_business' by being a discovery tool.

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?

Explicitly says 'Use this first to discover which agents to ask,' providing clear when-to-use guidance. Lacks explicit when-not or alternatives, but context with siblings implies sequence.

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