marketplace

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

With no annotations, the description carries the burden of disclosing side effectsasha. It mentions authentication and billing, giving some behavioral clarityverträglich. However, it does not state potential side effects of the API call (e.g., data modification), error handling, or rate limits. For an execution tool, this is partial transparency.

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, consisting of two focused sentences that convey the action, authentication requirement, and billing implications. No redundancy 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?

The description covers essential context: what the tool does (executes endpoint), required auth setup, and billing. It also implicitly instructs the agent to refer to get_api and get_endpoint for path and argument details. It does not mention output format or error behavior, but for an API execution tool this may be acceptable given the schema and sibling references.

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 provides thorough descriptions for all four parameters. The path references get_api, arguments references get_endpoint, and slug and method are clearly defined. This leverages sibling tools for complete documentation, ensuring the agent knows exactly how to supply each 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 clearly states the tool's function: 'Execute one endpoint of a marketplace API through the live gateway.' It specifies the verb (execute) and resource (endpoint of a marketplace API), and distinguishes it from sibling tools like get_api or search_apis by focusing on execution rather than listing or retrieving metadata.

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 context for when to use the tool (to execute an actual API call) and notes the prerequisite of a JoJ API key. It does not explicitly exclude cases or point to alternatives, but the mention of live gateway and billing implies these are production calls grants clear usage context. Could be improved with explicit statements like 'use get_endpoint to inspect parameters first'.

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 content of the overview (endpoint list, plans, links), but does not mention whether the operation is read-only or any other behavioral details. Overall, it provides moderate transparency but could be more explicit about side effects or resource access.

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 front-loaded: it states the purpose and key contents in one sentence. It is efficient, with no wasted words. Could be slightly more structured, but it's well done.

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 one parameter and no output schema, the description covers the essential information: what it returns (overview, endpoint list, plans, links). It doesn't mention return format or pagination, but given the simplicity tear, it's fairly 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 coverage is 100% for the single parameter 'slug', and the schema description already explains it as 'The API's marketplace slug, e.g. from search_apis.' The tool description does not add additional meaning beyond that, so it meets the baseline of 3.

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 purpose: 'Overview of one marketplace API by slug' and specifies what the overview contains (what it does, endpoint list, plans, links). This distinguishes it from siblings like search_apis (for searching) and get_endpoint (for a specific endpoint).

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 by stating 'by slug' and gives an example ('e.g. from search_apis'), indicating a typical workflow where a slug is obtained from a search. It does not explicitly exclude alternatives or state when not to use it, but the context is clear enough for selection.

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, the description must convey the tool's behavior. It explains what the returned documentation covers (parameters, request body, responses, billing), but does not explicitly state that it is read-only or mention potential side effects or authorization requirements. The 'documentation' wording strongly implies read-only, but the absence of explicit disclosure is a minor gap.

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-rich sentence that front-loads the tool's purpose and lists its key outputs without wasted words.

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 no output schema, the description sufficiently outlines the return content (parameters, request body, responses, billing). It is complete for a low-complexity documentation tool and aligns with sibling tools like call_endpoint, though it does not mention error behavior or prerequisite actions.

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 already provides 100% coverage of the three parameters with clear descriptions, so the description adds no extra parameter-level detail. This meets the baseline of 3 for well-covered schemas.

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 ('endpoint documentation'), and clarifies that it covers one endpoint, distinguishing it from siblings like get_api (which likely lists endpoints) and call_endpoint (which invokes 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?

The phrase 'for one endpoint of a marketplace API' clearly implies use when full details about a specific endpoint are needed, which differentiates it from listing all APIs or searching. It does not explicitly state when not to use it, but the context is clear enough.

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?

There are no annotations, so the description must carry transparency. It states the tool returns matching APIs, implying a read-only operation, but it never explicitly says it does not modify data or have side effects. It also does not mention rate limits, errors, or pagination, leaving some behavioral aspects unspecified.

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, consisting of two sentences that efficiently convey the tool's purpose and output. It avoids unnecessary details, making it easy to read and understand.

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, combined with the schema, gives a basic understanding of the tool but lacks explicit guidance on when to use it over sibling tools and does not elaborate on the meaning of sort and limit. It is adequate for a simple search function but not fully comprehensive for a user new to these tools.

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?

Only the 'query' parameter has a schema description, leaving 'sort' and 'limit' without explanation. The tool description does not compensate for this low coverage; it provides no additional detail about how sort or limit affect results. Since schema description coverage is below 50% and the description adds no parameter-specific meaning, the score is low.

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 that this tool searches the JoJ API marketplace, lists the types of APIs covered, and mentions it returns matching APIs with slugs and links. This distinguishes it from sibling tools like get_api or call_endpoint, which likely focus on retrieval or invocation.

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 discovering APIs but does not explicitly state when to use this tool instead of its siblings. It lacks direct guidance such as 'use this to find APIs before calling them' or comparisons to get_api/get_endpoint. The context is clear, but explicit contrast is missing.

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