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?

With no annotations provided, the description carries the burden of explaining behavior. It discloses that the directory is public, that only top matches are returned, and lists the returned fields including the canonical page URL. It does not discuss rate limits, result limits, or failure behavior, but the disclosed information is meaningful and accurately reflects the tool's read-only search nature.

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 with no filler. The core action and scope are front-loaded, and the examples at the end clarify query formulation without bloating the 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?

The description is complete enough for a search tool: it explains what is searched, what is returned, and how to construct queries. There is no output schema, so the explicit mention of return fields is valuable. It could be slightly stronger with a note about limiting results or differentiating from sibling tools.

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 beyond the schema by advising the agent to use the customer's own natural-language wording and by showing how location, service, and language can be embedded in the query text, which helps with using the query parameter effectively.

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 Pro public business directory and returns matching business entries, which is a specific verb-resource pairing. It is distinct from the sibling get_business by implication (search vs. retrieval), but it does not explicitly call out how it differs from ask_directory.

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 gives clear guidance on how to formulate queries, including concrete examples like 'manicure in Alicante' and 'online QA course in Russian.' However, it does not explain when to prefer search_businesses over the sibling tools ask_directory or get_business.

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