SynergyBoat

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

The readOnlyHint annotation already covers safety, and the description adds no additional behavioral detail beyond the lookup itself. It does not disclose error handling or return format, but for a simple read operation this is acceptable given the annotation coverage.

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, front-loaded sentence with no wasted words. It states the action, resource, and source clearly, making it highly concise and well-structured.

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 getter with readOnlyHint, the description is adequate. It does not explain the return structure, but the presence of sibling list tools and the straightforward nature of the operation make the description sufficient for most use cases.

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 100% coverage with a description for the slug parameter. The tool description repeats this information without adding extra semantics, so it aligns with the baseline for high schema coverage.

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 (Get) and resource (SynergyBoat case study) with a clear identifier (slug). It also names the source list (list_case_studies), distinguishing it from sibling list tools. This makes the tool's purpose immediately obvious.

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 provides clear contextual guidance by specifying that the slug comes from list_case_studies, implying a prerequisite call. It does not explicitly state exclusions or alternatives, but the reference to list_case_studies effectively directs the agent on correct usage versus listing all case studies.

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 declare readOnlyHint=true, and the description's 'Get' phrasing aligns with this. It adds value by enumerating the exact data points returned (what the company does, founders, contacts, service areas, rating), which informs the expected output without contradicting the annotation.

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 immediately states the action and resource, then lists the key content areas. Every word contributes meaning without unnecessary detail.

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, zero-parameter tool with no output schema, the description fully covers what the tool returns and its scope. It provides enough information for an agent to select and 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?

The tool has zero parameters, so the schema is empty and coverage is 100%. The description does not need to explain parameter behavior; the baseline of 4 for zero-parameter tools 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?

Clearly states the tool retrieves a factual overview of SynergyBoat, listing specific content areas (founders, contact channels, service areas, rating). This distinguishes it from sibling tools like list_services and list_team, which focus on narrower categories.

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 that this tool is for a company-level overview, so an agent can infer when to use it. It does not explicitly name alternatives or exclusions, but the scope is unambiguous given the sibling tools.

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 adds behavioral context beyond the readOnlyHint annotation by stating the response includes the full service object ('in full') and that the id originates from list_services. This provides useful workflow and return-scope information without contradicting 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?

A single sentence that is direct and free of redundancy. It front-loads the action and resource, making it immediately clear the agent needs.

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 get-by-id tool with a readOnlyHint annotation and fully described schema, the description adequately covers the purpose, id source, and return scope. No output schema is needed, and no critical information 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% with descriptions for both id and locale. The description repeats that id comes from list_services but does not add new parameter semantics beyond what the schema already 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?

The description clearly states the tool retrieves a single SynergyBoat service by its id, using the specific verb 'get' and resource 'service'. It also distinguishes itself from list_services by indicating this returns one full service rather than a list.

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 from list_services' explicitly tells the agent to first call list_services to obtain the id, establishing a clear workflow. It implies this tool is for fetching a single record vs. listing all, though it does not explicitly name alternative tools.

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 covers the safety profile, and the description adds the list of output fields, which is useful. However, it does not disclose any additional behavioral traits such as ordering, pagination, or whether the list is dynamic. This is adequate but not rich.

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, front-loaded sentence that conveys the action, resource, source, and key fields without any fluff. Every part of the sentence adds value.

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 zero parameters, a readOnly annotation, and no output schema, the description fully covers what a caller needs to know: it describes the list and explicitly names the returned fields (slug, title, category, overview). This is complete for such a simple tool.

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, so the baseline is 4. The description focuses on output fields rather than parameters, but no parameter explanation is needed. It adds context about what the returned data contains, which is beyond the schema's empty property list.

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 ('List') and resource ('SynergyBoat AI capabilities and use cases'), and differentiates from sibling tools like list_services and list_case_studies by specifying the source ('AI hub') and the returned fields (slug, title, category, overview). This is a specific and unambiguous purpose.

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 by specifying the source ('as shown on the AI hub'), which implies the intended use case. However, it doesn't explicitly say when not to use this tool or mention alternatives, so it misses the highest bar for explicit guidelines.

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 readOnlyHint=true, so the description doesn't need to state safety. It adds value by disclosing the exact output fields (slug, title, client, industry, outcome summary), which is behavioral context beyond what annotations provide. No contradictions.

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 no fluff. The first sentence states the action and output, the second gives an alternative. Information is front-loaded and every word 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 simple list tool with one optional parameter and a readOnly annotation, the description is complete: it lists output fields and directs users to get_case_study for full details. No output schema exists, so outlining the fields in the description is sufficient.

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 only parameter 'limit' is fully described in the schema with default value, so schema coverage is 100%. The description adds no extra parameter information, but the baseline of 3 is appropriate when the schema does the heavy lifting.

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 lists SynergyBoat case studies with specific fields (slug, title, client, industry, outcome summary). It distinguishes itself from sibling get_case_study by explicitly indicating that tool is for full details.

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 provides direct usage guidance: use this tool for listing multiple case studies, and use get_case_study for a single full case study. This explicitly names an alternative and clarifies when to choose each.

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 covers safety, and the description adds source context ('as shown on synergyboat.com') and the output fields. However, it does not disclose any additional behavioral traits such as locale defaulting or pagination limits, though none are necessarily expected for a simple list operation.

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 concise, front-loaded sentences cover purpose, source, output content, and the sibling alternative. Every word earns its place, and there is no fluff or repetition.

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 parameter and no output schema, the description adequately states the output fields and points to the detailed sibling tool. The locale parameter is covered by the schema, so the overall context is complete enough for an agent 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?

The schema fully describes the only parameter 'locale' with an explicit description and enum values. The description adds no parameter-specific meaning, but with 100% schema coverage, 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 states a specific verb ('List'), a specific resource ('SynergyBoat services'), and the exact scope ('as shown on synergyboat.com'). It also lists the output fields (id, name, outcome summary) and explicitly contrasts with get_service, making the tool's purpose unmistakable.

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 points to get_service for full details, providing a concrete alternative. It implies this tool is for summary-level browsing but does not mention when to prefer other sibling list tools like list_ai_use_cases or list_case_studies.

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 covers the safe read nature. The description adds value by specifying the content fields and the source URL, providing useful behavioral context beyond the annotation.

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 purpose and lists the output fields with no wasted words. Every element 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 simple read-only list tool with no parameters, the description is complete: it explains what data is returned and where it comes from. The existing annotations and trivial schema leave no gaps.

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?

There are zero parameters, so schema coverage is trivially 100%. The description adds no parameter-specific details, but none are needed. Baseline 4 applies for 0-parameter 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 states the tool's function with a specific verb ('List') and resource ('the SynergyBoat team'), and enumerates the exact data fields (name, title, leadership, expertise, profile links). It is distinct from sibling tools like list_services or list_case_studies.

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 context is unambiguous: this tool is for retrieving the team listing from the website. It doesn't explicitly discuss alternatives or exclusions, but the tool's name and description make the intended use obvious among the sibling set.

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 adds meaningful behavioral context beyond the annotations: it explicitly requires user consent and states that a lead is created for follow-up. This goes beyond the raw mutation flags in the annotations. No contradictions found.

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 concise and well-structured: a single sentence stating the action and required fields, followed by a short sentence on the outcome and consent requirement. No wasted words, information 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 form submission tool, the description covers the essential aspects: purpose, required fields, consent requirement, and follow-up behavior. There is no output schema, but return values are not mentioned; however, this is acceptable for such a straightforward tool. The main gap is the lack of differentiation from submit_lead, but that is more of a usage guideline issue.

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 input schema already fully documents all six parameters. The description simplifies rather than adds new meaning; it just lists the fields. Baseline 3 is appropriate since no additional semantic depth is provided.

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 action ('Request a SynergyBoat demo') and lists the key fields involved, making the tool's purpose evident. However, it does not explicitly distinguish this from the sibling tool 'submit_lead', which also appears to create leads, slightly reducing clarity.

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 provides no guidance on when to use this tool versus alternatives like 'submit_lead'. It only mentions that it creates a lead, which is a consequence, not usage context. There are no exclusions or alternative recommendations.

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 indicate non-read-only, non-idempotent, and non-destructive behavior. The description adds useful context: it creates a lead, which the team follows up on, and explicitly requires user consent. This goes beyond the annotations to explain the consequence of use.

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 two sentences, front-loaded with the action verb, and every sentence adds value. It is concise, efficient, and free of superfluous content.

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 full parameter descriptions, annotations, and no output schema, the description covers the essential behavioral context: what it does, what it creates, and the consent requirement. It does not describe the response format, but that may not be critical for this simple mutation tool.

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 each parameter is already documented. The description restates the main fields (name, email, enquiry, consent; optional company) but adds no new semantic meaning beyond what the schema provides, such as format or validation rules. Baseline 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 uses a specific verb ('Submit') and identifies the resource ('contact enquiry to SynergyBoat'), listing the key fields. It clearly states the tool's function, but it does not explicitly differentiate from sibling tools like request_demo, which could also capture a lead.

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 usage for contact enquiries and includes a prerequisite ('Requires explicit user consent'), but it does not explicitly state when to use this tool instead of request_demo or other siblings. No exclusions or alternatives are provided, making the guidance somewhat implicit.

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