Laspi Business Directory

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

Describes key behaviors: LLM-reranking, strictly from directory (never invented), and grounding links. No annotations exist, so description carries the burden; it's mostly transparent but lacks side effects or permission details.

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 concise sentences covering purpose, output, and usage guidance. No wasted 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?

Given two parameters and no output schema, the description fully explains input, output format (schema.org cards + grounding links), and behavior (LLM-reranked, no invention). No missing critical info.

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 parameter descriptions. The description adds little beyond clarifying that 'question' is a natural language query. Baseline 3 appropriate since schema is already sufficient.

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 answers customer questions in natural language, returning schema.org cards of relevant businesses. Differentiates from sibling tools (search_businesses likely keyword-based, get_business specific) by focusing on natural language needs.

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 advises when to use: when the customer describes a NEED rather than a search term. This provides clear guidance vs. sibling tools.

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 adds value by specifying return content (description, services, contacts, languages) and source of slug, though does not explicitly state read-only nature or auth requirements. Still, it's adequate for a simple retrieval 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?

Single concise sentence that is front-loaded with the core action and includes all essential details without any 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?

Given no output schema, the description adequately explains what is returned (description, services, contacts, languages). For a simple one-parameter retrieval tool, it is complete and informative.

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 already describes the slug parameter with 100% coverage. Description adds context on where the slug originates (search results or URL), providing meaning beyond 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?

The description uses specific verb and resource ('Get the full public card of one business'), lists content types, and distinguishes from siblings by focusing on a single business lookup via slug.

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?

Clearly states the tool retrieves a business card by slug, implying usage when slug is available, but lacks explicit when-not-to-use or comparison with sibling tools ask_directory and search_businesses.

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, and the description does not disclose behavioral traits such as read-only nature, rate limits, pagination, or authentication requirements. The description only states that it returns top matches, which is minimal disclosure.

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 very concise at two sentences. It is front-loaded with the core action and resource, and every sentence serves a purpose without superfluous text.

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 lack of an output schema, the description lists the returned fields (name, description, city, languages, URL), which is helpful. The tool has 4 parameters, and the description covers essential usage context, though ordering or result limits are not mentioned.

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 baseline is 3. The description adds value by providing usage examples and emphasizing natural-language queries, but does not significantly expand on the parameter descriptions already present 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?

The description clearly states the tool searches the Laspi public business directory and returns matches. It uses the verb 'Search' and specifies the resource. It does not explicitly differentiate from siblings 'ask_directory' and 'get_business', but the purpose is well-defined.

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 an example of how to formulate queries and advises using the customer's own words. However, it does not give guidance on when to prefer this tool over its siblings, nor does it mention scenarios where it should not be used.

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