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

Annotations declare readOnlyHint=true, consistent with a read operation. Description adds that the tool handles typos and partial names, and returns specific data fields (routes, ratings, etc.). No contradictions, and it provides context 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?

Description is three sentences, front-loaded with the main purpose, then details about typo handling and return fields, and ends with a sibling alternative. Every sentence adds value with no redundancy.

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 no output schema, the description clearly lists return fields (licence routes, ratings, locations, register dates). Parameter details are sufficient. Tool complexity is low, and the description fully covers what the agent needs to use it correctly.

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 schema already documents both parameters. Description redundantly repeats the 'typos OK' for company_name and explains country parameter briefly. Adds no new meaning beyond what the schema provides.

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 if a company holds a UK or Netherlands work-visa sponsorship licence, specifies handling typos/partial names, and lists return fields. Distinguishes itself from sibling 'search_sponsors' by contrasting use cases.

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 to use this for checking a single company and suggests 'search_sponsors' for exploring/filtering many companies. Lacks explicit when-not or exclusions, but the guidance 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?

The readOnlyHint annotation already indicates a safe read operation. The description adds value by specifying the scope (statistics, freshness, terminology) and the UK/Netherlands geographic focus. It does not introduce any behavioral contradictions or unexpected side effects.

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 the core function front-loaded and a practical usage example. Every word earns its place, and there is no redundant repetition of the tool name or schema.

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 zero-parameter, read-only informational tool, the description provides adequate context about what the tool returns and when to use it. While there is no output schema, the description names the key content areas, making the return structure predictable enough for an agent.

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 tool has 0 parameters, so parameter descriptions are unnecessary. The baseline of 4 applies because there is nothing to explain; the description's focus on content 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 tool provides register statistics, data freshness, and terminology for UK and Netherlands sponsor registers. It also gives a concrete use case ('explain what a licence, route, rating, or sponsor type means'), which distinguishes it from sibling tools focused on checking licenses or searching for sponsors.

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 includes a direct usage instruction ('Use this to explain...'), which gives a clear context for when to invoke this tool. While it does not explicitly mention alternatives or exclusions, the context is strong enough to guide selection among siblings.

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?

The readOnlyHint annotation already signals a safe read operation. The description adds behavioral context by listing exactly what fields are returned and noting country-specific differences (UK vs NL) and the optional history flag. This goes beyond the annotation without contradicting it.

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, information-dense sentence with no filler. It front-loads the core purpose ('Full record for one organization by id') then appends specifics, making it easy to parse and remember.

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 detail retrieval tool with 3 parameters and no output schema, the description covers the essential purpose, key data fields, and country-specific behavior. It does not discuss error handling or pagination, but these are not critical given the tool's simplicity and the readOnlyHint annotation.

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% description coverage for all three parameters. The description adds value by explicitly linking the country parameter to the different data returned (routes/ratings vs sponsor type/KvK) and reinforcing the include_history parameter's purpose. This enriches the parameter meanings 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 starts with 'Full record for one organization by id', clearly specifying the resource (sponsor record) and the action (retrieve). It distinguishes itself from siblings like search_sponsors by emphasizing lookup by id and enumerating specific content (routes, ratings, locations, register dates, sponsor type, KvK number).

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 phrase 'by id' implies this is for retrieving details when an org_id is already known, and the country parameter clarifies which register to query. 'Optionally include register change history' gives a usage hint. However, it does not explicitly name alternatives or state when not to use this tool, leaving some inference needed.

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 annotations providing readOnlyHint=true, the description adds value by disclosing the output behavior: returns a 'compact list with a total count'. This goes beyond the annotation's safety info and gives the agent a clearer expectation of the tool's result shape, though it doesn't mention pagination or potential limitations.

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 exceptionally concise, with two sentences that front-load purpose, then mention output and an alternative. Every word adds value, with no repetition of schema or annotation details.

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 tool's moderately complex parameter set (though all optional) and lack of output schema, the description covers essential aspects: purpose, return shape, and an alternative. It could mention pagination or the meaning of 'compact list', but overall it sufficiently contextualizes the tool 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?

The schema already provides full descriptions for all six parameters (100% coverage), including country-specific filters. The description reinforces the filter groupings but doesn't add substantial meaning beyond the schema, so a baseline score of 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 tool performs an 'Exploratory list search of the sponsor register' with specific resources and optional filters. It also distinguishes from sibling tool check_sponsor_license by directing users to that tool for checking a specific company, making purpose and scope unambiguous.

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 guidance is provided: use this for exploratory list searches, and specifically prefer check_sponsor_license for verifying a single company. The description also notes country-specific filters (UK vs NL), helping the agent choose when to use it with appropriate parameters.

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