Marketingburos

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

With no annotations present, the description carries the full burden and does a good job: it discloses the maximum of 10 candidates, the returned fields (name, legal_name, city, domain), and the fact that legal_name appears only when it differs from the statutory name. It does not mention edge cases like no matches or behavior when no parameters are provided, but the core behavior is transparent.

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 compact, front-loaded with the search purpose, and adds only high-value details: examples, output fields, the slug link, and the sibling alternative. Every sentence earns its place with no filler.

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 lookup tool with low complexity and no output schema, the description gives enough context: search criteria, examples, returned fields, result cap, and an explicit pointer to a sibling for ranked use. It could be slightly more complete by explaining the city and limit parameters, but it is otherwise well-rounded.

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 has 0% description coverage, so the description must compensate. It explains name and domain with concrete examples, but it does not explain the city parameter or the limit parameter in terms of how they affect the search. The mention of 'max. 10 kandidaten' hints at limit's upper bound but does not clarify that limit is configurable or that city is an optional filter.

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 finds a specific agency by handelsnaam, statutaire naam, or domain, and that it produces the slug needed for get_agency_profile. It also distinguishes itself from search_agencies by positioning itself as the targeted lookup option rather than a ranked recommendation 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?

The description explicitly says to use search_agencies for ranked agency advice based on criteria, which makes the boundary between the two tools clear. It also implies the correct workflow: find the agency to obtain the slug, then use get_agency_profile.

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 full burden of behavioral disclosure. It adds valuable behavioral context beyond the schema: the tool returns a 404 both when the slug does not exist and when the agency has opted out of MCP reachability. This is a meaningful non-standard behavior for an agent to know. It could go further by describing the response format, but for a simple read operation this is solid.

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 compact and effective: one sentence states the main action, the second gives the key error condition. Both sentences earn their place, and the primary purpose is 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 single-parameter read tool with no output schema and no annotations, the description covers the essential decision factors: what it does, what identifies the target, and when it errors. It does not describe the response structure, but 'volledige publieke profiel' sufficiently signals the returned content type for an agent to call 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 description coverage is 0%, so the description must compensate. It does clarify that slug is the identifier used to look up the profile, which adds some semantic value beyond the raw string schema. However, it does not describe slug format, casing, or URL relevance, so the compensation is only partial.

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 states a specific verb ('Haal ... op' - retrieve) and resource ('volledige publieke profiel van een marketingbureau') keyed by its slug. This clearly distinguishes it from the sibling find/search tools, which are for discovery rather than retrieval of a full profile by exact identifier.

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 implies when to use the tool: when you already have an agency's slug and need its full public profile. However, it does not explicitly contrast with find_agency or search_agencies, nor state when not to use it, so the routing guidance is implicit rather than explicit.

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 present, the description carries the full burden and does so thoroughly: it discloses hard taxonomy filtering, unmatched specialism behavior, the all-unknown case yielding zero results plus a hint, budget_band's conflict-based exclusion, the 20-result cap, ranking, and the totalMatched field. This is unusually transparent.

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 dense but well-organized: purpose first, then filter semantics, then caveats, output shape, and a pointer to valid values. Every sentence adds necessary information, though the first long sentence packs many clauses and could be slightly harder to parse.

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 an 11-parameter tool with no annotations and no output schema, this description covers input semantics, edge cases, result limits, returned fields, and where to find valid enum values. An agent has enough information to select and invoke the tool 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 description coverage is 0%, so the description must compensate. It does meaningfully explain target_industry, specialisms, the two radius modes, within_km, budget_band semantics, and the output fields. It does not elaborate on limit or the exact enum values, though it points to categories://list for those, so it is strong but not maximal.

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 opens with a specific verb and resource ('Zoek Nederlandse marketingbureaus') and enumerates the exact filter dimensions. It clearly positions this as a multi-criteria search returning a ranked list, which distinguishes it from sibling tools like find_agency or get_agency_profile 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?

It gives concrete guidance on how to use the filters, including the optional radius alternatives and the instruction to read categories://list for valid values. It does not explicitly say when NOT to use this tool or name alternatives as better fits, so it stops short of a 5.

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 behavioral disclosure. It usefully reveals that submissions go to a Phase 5 release-queue and require manual operator release, implying asynchronous behavior. However, it does not mention side effects, confirmation behavior, error conditions, or whether the submission is immediately accepted.

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 compact and front-loaded with the core action. The second sentence adds meaningful queue/release context without unnecessary verbosity. Every sentence earns its place.

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 complex 17-parameter mutation tool with no output schema and no annotations, this description is incomplete. It does not explain required inputs, success/failure semantics, response format, or what the agent should tell the user after submitting. The queue detail is helpful but insufficient on its own.

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 0%, and the description provides no parameter-level guidance. With 17 parameters and 12 required, the agent receives no help understanding what fields like `specialisms`, `culturalFit`, `selectedAgencyIds`, or `specialistFullServiceSlider` mean or how to populate them.

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 a specific action: submitting a Request-For-Quote to marketingburos.nl. It is easily distinguished from the sibling tools, which are all search/read-oriented (find_agency, get_agency_profile, search_agencies), while this is a submission 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?

The description does not state when to use this tool versus the sibling search tools. It gives context about the request being queued and manually released, but lacks explicit guidance on prerequisites, selection flow, or when an agent should instead use the lookup tools.

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