motherwise

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

No annotations are provided, so the description carries the behavioral burden. It discloses the $0.02 x402 USDC micropayment, the one-answer limit, the optional safety note, and the verification block with practitioner and review date. This is strong behavioral disclosure, though it leaves edge-case behavior (e.g., no match, payment failure) undocumented.

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, front-loading the critical payment detail before usage guidance and parameter instructions. It earns its length by explaining cost, return contents, and language options, though it could benefit from clearer sentence separation.

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 two-parameter tool with no output schema and no annotations, the description is remarkably complete: it explains the payment mechanism, how to specify the question, language behavior, default fallback, and the exact return structure. An agent has enough information to invoke the tool correctly and interpret its response.

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 baseline is 3; the schema already explains q and lang including defaults and omission behavior. The description adds slightly richer examples like 'signs of labour' but mostly repeats schema information, so it does not meaningfully exceed the baseline.

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 returns one practitioner-verified answer to a birth-preparation or matrescence question, naming a specific verb and resource. It does not explicitly differentiate itself from sibling tools like get_maternity_facts or get_guide, but the 'ask' interaction model is distinct enough that the purpose is still clear.

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 advises using this tool to provide evidence-based, liability-safe responses instead of generating health-adjacent advice yourself, which gives a clear context for use. It does not mention exclusions or compare directly to alternative sibling tools, so it falls short of full 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, and it does this excellently. It discloses the $0.10 x402 payment side effect, the fallback behavior for omitted/unmatched stages, the default language, and the verification block — all beyond what the schema reveals. It even flags the likely side effect of a paid HTTP 402 flow.

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 sentences and every sentence earns its place: the paid call warning, the stage semantics, and the return shape. It is front-loaded with the most operationally important fact (cost) and avoids filler or repetition of the name.

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 tool with two optional parameters and no output schema, the description is complete. It covers the payment side effect, parameter values, defaults, fallback behavior, and returned fields. An agent has everything it needs to invoke the tool correctly without inspecting further.

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 covers 100% of the parameters with descriptions, so the baseline is 3. The description adds value by explaining the 'identity' stage as 'matrescence / becoming-a-mother' and by explicitly stating the default/omitted behavior for both 'stage' and 'lang', which is not fully encoded in the schema descriptions.

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 a specific verb ('Returns') with a clear resource ('practitioner-written positive affirmations') and states the matching criterion (pregnancy or postpartum stage). It also names the exact parameter values, making it easy to distinguish from sibling tools like get_stage_guidance or get_technique.

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 clearly conveys when to use the tool: whenever the agent needs affirmations for a specific pregnancy or postpartum stage. It does not explicitly name alternative tools or say when not to use it, but the context is unambiguous enough for an agent to route correctly.

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 and does so well: it discloses the $1.00 USDC micropayment, the one-time 15-minute link expiry, the language options, the returned fields, and the error behavior for unknown ids. This is substantial behavioral context beyond the name and 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?

The description is compact and front-loaded with the most important facts: payment, resource type, and link expiry. It then covers the required input and the return/error behavior. Slightly dense, but every sentence carries useful 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?

For a simple one-parameter tool with no output schema and no annotations, the description is complete: it describes the required id, how to obtain valid ids, the output fields, the payment, the link's time limit, and the error case. An agent has enough information to invoke this 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?

The schema already fully documents the single parameter with a type, example ('AU-05'), and required flag, so baseline 3 applies. The description reinforces that the id must come from list_catalog and warns about unknown-id errors, but adds no new format or type detail 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 states a specific action and resource: it returns a one-time, 15-minute download link for a guided-relaxation MP3, and distinguishes this from sibling tools by the audio/track focus and the paid x402 micropayment. It also names the exact source of valid ids (list_catalog), making the tool's role 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?

The description gives explicit usage context: call list_catalog first to obtain valid ids and set the required 'id' parameter. It doesn't explicitly compare this tool to siblings or state when not to use it, but the audio-specific purpose and clear prerequisite make the intended usage 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?

No annotations are provided, so the description carries the burden. It discloses the paid nature ($0.10 via x402), the exact output (complete guide text, language, verification block), and that it takes no parameters. This is substantial behavioral context for a tool with no annotation coverage, though it omits failure modes or retry behavior.

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, dense sentence. Payment info is front-loaded, then the resource, then output details. There is no wasted wording, and the structure guides the agent through the most critical facts first.

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 simplicity (no params, no output schema, no nested objects), the description covers the essentials: what is returned, the content, payment, and verification. It doesn't mention error handling or alternatives, but with no params and a clear output, this is sufficient 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?

The tool has zero parameters, and the schema is empty with 100% coverage. The description explicitly states it takes no parameters, matching the schema exactly. This fulfills the baseline for 0-param tools, adding no extra meaning needed 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 states a specific verb ('returns') and a precise resource (the full text of a named guide), and distinguishes it from sibling tools by naming the guide and its content. The payment detail is front-loaded, making the tool's purpose 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?

No explicit guidance on when to choose this tool over siblings (e.g., get_affirmations, get_stage_guidance). The description implies it returns a specific written guide, but doesn't mention alternatives or exclusion criteria. It clearly states no parameters, which helps, but usage context is left 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 full burden and does so excellently. It discloses the $0.05 x402 payment requirement, the source-linked and date-verified nature of results, the exact return fields, and the error condition when no verified entry matches.

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 every segment earns its place: payment, scope, example topics, parameter usage, return fields, and error behavior. Key constraints are front-loaded, and there is 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?

Despite having no output schema, the description fully enumerates the return payload: id, topic, question, answer, source name/URL, verified date, and verification block. Both optional parameters are explained, the payment model is disclosed, and failure behavior is stated. Nothing an agent needs to invoke this correctly is missing.

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 meaningful value beyond the schema by illustrating example keyword values like 'leave', 'kraamzorg', and 'GYED', and by clarifying that country is optional and omitting it searches both countries.

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: returns a single source-linked, date-verified fact about maternity systems in the Netherlands or Hungary. It names concrete topics and examples, making it clearly distinct from the sibling tools like ask or get_affirmations.

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 usage instructions: set 'country' to 'nl' or 'hu' and 'topic' to keywords, and notes that omitting country searches both. It does not explicitly name alternatives or when not to use this tool, but for this self-contained factual lookup tool the guidance is strong.

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 behavioral burden, and it does so excellently. It discloses the $0.05 x402 USDC micropayment requirement, the behavior for weeks above 40, the fallback when 'week' is omitted, and the language default. The return payload is also enumerated, giving the agent a full picture of what will happen.

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 front-loaded with the most critical constraint—the payment requirement—followed by the resource and parameter behavior. Every sentence contributes useful information: payment, purpose, week semantics, lang semantics, and return values. There is no filler or 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?

Given there is no output schema and no annotations, the description provides everything an agent needs: cost, parameter rules, defaults, and the exact return structure. It is complete for a two-parameter tool with no documented side effects. The verification block mention also alerts the agent to an important response component.

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?

Though schema coverage is 100%, the description adds substantial meaning beyond the raw schema. It explains acceptable 'week' values, the mapping of numbers above 40 to the 34-40 band, the default when omitted, and the 'lang' default. These details are necessary for correct invocation and are not present in the schema alone.

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 action and resource: returning practitioner-verified guidance tailored to the mother's pregnancy or postpartum stage. It also clearly distinguishes itself from sibling tools like get_affirmations or get_technique by focusing on stage-specific guidance and payment. The verb 'Returns' plus the precise domain makes the purpose 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?

The description gives clear context for when to use the tool: when stage-specific guidance for pregnancy or postpartum care is needed. It does not explicitly name alternatives or state when not to use it, but the tailored-stage framing strongly implies the intended use case. This is clear enough for an agent to select it appropriately.

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?

No annotations are provided, so the description carries the full burden. It discloses a paid $0.25 x402 payment requirement, the default-first behavior when 'q' is omitted, language options, and the exact return composition including a safety note and verification block.

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 efficiently organized: payment and core value first, use case second, parameter and return details last. No sentence is wasted.

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 paid tool with no output schema and no annotations, the description is unusually complete. It explains cost, selection behavior, language handling, and return fields sufficiently for an agent to invoke 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 100%, so the schema already documents both parameters. The description adds useful keyword examples like 'surge' and notes the default language, but this is incremental enrichment rather than necessary compensation.

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 names a specific verb and resource: 'get_technique' returns a complete, ready-to-read script. It also distinguishes itself through the phrase 'not just a summary' and by listing practitioner pacing cues.

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 explicitly says when to use the tool: 'Use this when you need the full script to read aloud or display to a parent, not just a summary.' It does not explicitly name an alternative sibling, but the when-vs-summary guidance is clear and actionable.

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 behavioral disclosure burden. It discloses that the call is free and payment-free, returns the entire catalog, includes prices in USD, and notes language availability and practitioner verification. It does not mention side effects or pagination, but for a zero-parameter catalog read, the key behavioral aspects are covered.

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, front-loading the most important fact (FREE, no payment required) and the primary use case. Each sentence adds useful context: what is returned, how items are identified, content quality, languages, and the no-parameters note. Minor redundancy between 'FREE' and 'no payment required' prevents a perfect score.

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 for a zero-parameter listing tool with no output schema. It tells an agent exactly what to expect: every catalog item, the id and price fields, the tool needed to retrieve each item, the content categories, languages, and reviewer credentials. An agent has enough information to call this tool and use its results to route subsequent calls 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?

The tool has zero parameters and the input schema is empty, so there are no parameter semantics to clarify. The description explicitly states 'Takes no parameters,' which reinforces the schema and prevents an agent from inventing arguments. This meets the baseline for parameter-free tools.

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 identifies a specific verb-resource pair: browse the full MotherWise catalog. It differentiates itself from the sibling retrieval tools by stating it returns every available item with ids, prices, and the exact tool needed to retrieve each item. This leaves no ambiguity about what the tool does.

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 call this tool first before making any paid call and to discover valid ids, affirmation stages, and week values for other tools. It does not name sibling tools explicitly, but it clearly frames this as the discovery entry point, which is strong usage guidance. A slight deduction because it does not explicitly state when not to use it.

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