Merchant Context

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world, so the safety profile is covered. The description adds valuable content-level transparency: it enumerates what the record contains (facts, verdict, source URL, check date, cross-source conflicts, View Google Listing link) and explicitly excludes Google review text, ratings, and listing values. This is richer than average, though it could mention pagination or output size for a 'full record'.

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?

A single dense sentence followed by a short second sentence for the parameter source. Front-loads the what/when well. Slightly long within the first sentence but every clause carries content-specific 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?

With an output schema present and annotations covering behavior, the description is complete: it explains the call context, input provenance, contents, and exclusions. Nothing critical is missing for correct invocation.

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% and the lone parameter is fully documented with an example in the schema itself. The description adds the provenance context ('state licence number from a search_businesses or verify_business result'), which is helpful but overlaps with the schema's example. Baseline 3 per rubric.

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?

States a specific verb (get) and resource (business evidence record), and clearly distinguishes itself from search_businesses and verify_business by positioning it as the deep-dive after finding a business. The scope is well-defined: full evidence record with facts, verdicts, sources, and conflicts.

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 when to use it ('when you need the complete evidence record behind a search result') and names the upstream siblings as the source of the input, creating a clear call sequence. Implied exclusion of Google review text/ratings further narrows its purpose.

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 declare the read-only, idempotent, non-destructive, open-world profile, yet the description still adds real behavior: results combine multiple independent sources, data is freshly read (booking pages 'minutes ago'), and conflicts between sources are surfaced rather than hidden. It also tells the agent what to lead with when urgency is the constraint.

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?

Front-loaded well — usage and routing come first — but the returns sentence is a 12-item run-on crammed into one paragraph, and an output schema already exists to document return fields. The long enumerated job list also bloats the opening. Dense and useful, but not tight.

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 read-only search with a full output schema and 100% schema coverage, the description is nearly complete on when to call it, what to pass, and what comes back. The one missing piece is disambiguation from its actual siblings get_business and verify_business, which the agent must guess at.

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, but the description adds genuine semantic guidance beyond the schema: ZIP drives distance and coverage matching, and query should carry the user's own constraint words ('weekend', 'tankless water heater'). That is more than the schema's terse 'user's constraints in plain words'.

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?

Names a specific verb and resource (search licensed local service businesses) and pins the scope tightly: four trades, one county, plus the exact job types covered. It distinguishes itself from the obvious non-sibling competitor (generic maps/local search) by naming the unique data assets it verifies — licence register, permit history, discipline record, cross-source conflicts.

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?

Explicit triggers ('who should I call', 'near me', a ZIP in the county), explicit exclusions ('Do not use for other trades or regions'), and a named alternative (generic maps/local search). The gap is sibling routing: 'Also use it to check the record of businesses found elsewhere' overlaps with verify_business/get_business and the description never tells the agent which of the three to pick, which is exactly the ambiguity that matters here.

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 declare readOnly/idempotent/non-destructive, but the description adds real behavioral content: the matching population (state licence register), the return shape (evidence record), and crucially the negative-case semantics — an explicit 'not in the state register' answer is itself the finding. That is not derivable from annotations or schema.

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?

Front-loaded with the trigger condition and tightly scoped, with the exclusion clause last. It is a single long em-dash-heavy run-on, and the quoted user phrasings are verbose, though they do serve recall for matching user intent.

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 one-param lookup with an output schema, nothing material is missing: data source, scope, trigger and negative result are all covered. Return-value detail is unnecessary given the output schema, and the description still summarizes it usefully.

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?

One parameter with 100% schema description coverage ('The business name as the user said it'). The description says to run each candidate's name through the tool, which corroborates the 'as the user said it' intent but adds no syntax, normalization, or formatting detail beyond the schema. Baseline 3 applies when the schema does the work.

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?

States a specific verb and resource (verify a named business against the state licence register) and nails the scope: HVAC/electrical/roofing/plumbing in Pinellas County, FL. The single-name verification framing is clearly distinct from the sibling search_businesses (population search) and get_business (retrieval), even without naming them.

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?

Explicit when-to-use ('whenever a user names a specific company ... and wants to know anything about it') with example phrasings, an explicit always-rule ('ALWAYS before recommending or elaborating on a company that came from maps/local search, web search, or the user's own list'), and an explicit exclusion ('Do not use for other trades or regions'). Alternative behavior (don't answer from search snippets) is named.

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