Taklo

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

With no annotations provided, the description carries the full disclosure burden. It does disclose one key behavioral trait: 'er wordt nog niemand echt teruggebeld totdat een mens het bevestigt' (nobody is actually called until a human confirms), which prevents a false expectation of immediate action. However, it says nothing about side effects beyond logging, permissions, or failure modes.

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 zero filler: the first states the action, the second clarifies the non-immediate behavior. Both sentences earn their place, and the critical caveat is front-loaded right after the action.

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 4-parameter tool with no output schema and no annotations, the description covers the essential caveat (request-only until human confirmation) but omits expected outcomes such as a confirmation or reference identifier, and any prerequisites. It's adequate for a straightforward request-logging tool but not complete.

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 only 25% (only voorkeursmoment has an example), falling below the 50% threshold, and the tool description adds no parameter explanation to compensate. The Dutch parameter names (naam, telefoon, reden, voorkeursmoment) are fairly self-explanatory, which softens the gap, but the description still leaves the semantics almost entirely to inference.

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 and resource: requesting that Evi (Taklo's AI receptionist) call someone back, with the clarifying distinction that it only registers the request rather than triggering a call. This makes the purpose clear and differentiates it by domain from the siblings (trial, info, integrations, pricing), though it doesn't name them explicitly.

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 trigger situation is implied rather than explicit: use this when someone should be called back by Evi. The description doesn't mention when not to use it or point to alternatives, but the sibling tools are so different in domain that confusion is unlikely.

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 available, the description carries the full behavioral burden, and it does this well: it explicitly says the tool does NOT create an account, returns a registration link with tracking query parameters, and requires the link to be passed unchanged for AI attribution. It omits response/error details, but the key safety and attribution behaviors are 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 three purposeful sentences: the goal, the key caveat that it does not create an account, and the critical instruction to pass the returned link unchanged. Every clause earns its place, and the most important behavioral distinction 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 simple four-parameter tool, the description covers the main action and a crucial instruction, but with no annotations, no output schema, and no parameter guidance it is not fully self-sufficient. A short note on when to prefer this tool over sibling tools and on how the inputs affect the generated link would complete it.

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, and the description adds nothing about naam, email, telefoon, or bedrijfsnaam. The agent is left to guess parameter meaning from property names and type/format hints; required versus optional semantics and how the values are used are not explained.

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's function: guiding the user through Taklo's 14-day free trial by returning a registration link and explaining how the trial works, rather than creating an account. It also clarifies the subscription-vs-quote scope, which helps separate it from pricing/quote flows, though it does not name any sibling tool explicitly.

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 intended use is implied clearly: call this when a user wants to start the free trial. However, there are no explicit when-to-use/when-not-to-use instructions or references to sibling tools such as taklo_info, taklo_prijs_berekenen, or plan_terugbelmoment, so selection guidance is left mostly to inference.

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 behavioral burden and does disclose 'Alleen-lezen' and 'geen persoonsgegevens nodig', which are meaningful. It does not describe return format or edge cases, but for a simple single-parameter info lookup this is acceptable.

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?

One front-loaded sentence states the purpose, lists supported topics, and adds safety context. Every phrase earns its place with no repetition or fluff.

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 low complexity, one enum parameter, and no output schema, the description provides everything needed to select and invoke the tool correctly: purpose, supported categories, read-only nature, and absence of personal-data requirements.

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 value by translating the enum values into plain business terms (fair-use-belminuten, bijkoopprijzen, proefperiode, algemene omschrijving). It does not explicitly mention the 'alles' option, though the schema covers that.

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 a specific verb and resource ('Zoek feiten op over Taklo') and enumerates concrete fact categories, making the tool's role unmistakable. It clearly contrasts with siblings like start_gratis_proefperiode and taklo_prijs_berekenen, which are actions rather than factual lookups.

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 states clear usage context: use this tool for read-only factual lookups and no personal data is needed. It does not explicitly name alternatives or say when not to use it, but the read-only framing and category list make the boundary with action-oriented siblings inferable.

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 description explicitly states 'Alleen-lezen, geen persoonsgegevens nodig', which is valuable behavioral context since no annotations are provided. It also discloses that the tool returns per-package activation requirements. It does not describe output format or error behavior, but for a simple read-only list tool this is adequate.

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, front-loaded with the main purpose, and the read-only/no-personal-data note is placed at the end. Every sentence earns its place; no fluff.

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 read-only list tool with one optional boolean parameter and no output schema, the description is nearly complete. It explains what the tool returns and the key distinction per package. It could mention the output format or what happens when the filter is omitted, but the schema already covers the parameter and the tool is simple enough that this is a minor gap.

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 100%, so the schema already documents the only parameter. The description adds context by explaining the output dimension (zelf aanzetten vs leverancier stap), which helps the agent understand the meaning of the boolean filter. Baseline 3 is exceeded slightly because the description clarifies the domain meaning of the parameter.

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 ('opvragen') and resource ('boekhoudpakketten waar Taklo mee koppelt'), and clearly distinguishes the tool's purpose from siblings like taklo_info or taklo_prijs_berekenen. It also specifies the key output dimension: per package, whether the entrepreneur can enable the connection themselves or whether a supplier step is needed.

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 this tool: when you need the list of accounting packages Taklo integrates with and the activation path per package. It does not explicitly name alternatives or exclusions, but the sibling names (taklo_info, taklo_prijs_berekenen) make the context clear enough. A small gap is the lack of explicit 'use this instead of X' guidance.

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 disclosing behavior. It explicitly states the tool is read-only ('Alleen-lezen') and requires no personal data, which is important safety information. It also mentions that amounts are exclusive of VAT, giving the agent an expectation about the output. This is sufficient for a simple read-only calculation 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?

The description is a single, well-structured sentence that front-loads the main purpose (calculating the monthly price) and then provides key additional details (breakdown, VAT, read-only, no personal data). Every element earns its place, and there is no redundancy or 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 tool with only one parameter and no output schema, the description is quite complete. It states what the tool does, the output structure (breakdown of base plus extra users), key constraints (VAT exclusive), and safety (read-only, no personal data). The only minor gap is that it does not specify the exact return format, but this is likely not required for such a simple calculation.

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 fully describes the 'gebruikers' parameter (type, min, max, description). The description adds meaning beyond the schema by explaining the pricing structure: 'bedrijfsbasis plus extra gebruikers' (company base plus extra users), which clarifies that the first user is included in the base. This enriches the parameter's semantics beyond the basic schema description.

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's function: calculating the monthly cost of Taklo for a given number of users. It specifies the resource (Taklo) and the action (calculate price), and distinguishes it from sibling tools like taklo_info, which is likely general information, and taklo_koppelingen, which is about integrations.

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 the tool is used when a user asks for the monthly price, but it does not explicitly state when to use it instead of alternatives or mention exclusions. No guidance is given about preferring this over taklo_info or other siblings, leaving the usage context implicit.

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