Qorevia Market Intelligence

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

With no annotations, the description carries the full burden of behavioral disclosure. 'Browse' hints at a read-only operation, but the description does not mention authentication requirements, response shape, pagination behavior, or whether it returns full tool metadata.

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 short and front-loaded with no wasted words, but it is under-specified for a tool with four parameters and no annotations. Its brevity reads more like a stub than a complete, useful definition.

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 four-parameter tool with no output schema and no annotations, this definition is too thin to invoke reliably. It lacks parameter semantics, category constraints, and any sense of what the returned catalog data looks like.

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%, yet the description adds nothing about q, limit, offset, or category. 'q' is especially ambiguous, and no acceptable category values are provided even though the schema has no enums.

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 'Browse' as a specific verb and identifies the resource as 'Qorevia live paid tools,' so an agent can infer this is a listing/catalog tool. It does not explicitly distinguish it from siblings like qorevia_find or qorevia_tool_info, but the catalog/browse framing provides reasonable separation.

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 guidance is given on when to use this tool versus alternatives such as qorevia_find for searching or qorevia_tool_info for inspecting a single tool. The appropriate context must be guessed from the tool name and sibling list.

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?

'Free discovery only' adds a meaningful behavioral constraint, suggesting the operation is non-mutating and cost-free. With no annotations, the description carries the burden of behavioral disclosure, and it is thin on details like output format or side effects, though 'discovery' implies a read-only search.

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 short and front-loaded, with the core purpose stated in the first sentence. 'Free discovery only' is a useful extra constraint, though the word 'best' is somewhat vague and not strictly necessary.

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 tool is simple with only two parameters and no output schema, but the description still omits essential context: no parameter semantics, no example of a natural-language query, and no guidance on what the agent should do with the result. It is minimally viable but leaves several important aspects to inference.

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 does not explain 'query' or 'limit' beyond what their names suggest. The natural-language framing hints at the query parameter but never explicitly states what format the query should take or how limit affects results.

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 verb and resource: 'Find the best Qorevia x402 tool for a natural-language need.' It conveys that this is a discovery/recommendation tool, but it does not explicitly differentiate itself from siblings like qorevia_catalog or qorevia_route.

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 a natural-language need' implies the tool should be used when an agent needs to map a user request to a suitable Qorevia x402 tool. However, there is no explicit guidance about when to prefer this over qorevia_catalog, qorevia_route, or qorevia_tool_info, and no when-not-to-use conditions.

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 must carry the full burden of disclosing side effects, safety, and behavior. It only states that a call plan is returned, which implies a read-only computation, but it does not explicitly say whether it is safe, requires authentication, or has any side effects. The lack of detail leaves significant ambiguity for an agent deciding to invoke it.

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, concise sentence that is easy to parse and front-loads the core action. However, it is too sparse given the tool's complexity and the absence of annotations. It is under-specified rather than appropriately concise, so it does not earn a higher 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 tool has 2 parameters, no output schema, and no annotations, so the description must be comprehensive to enable correct invocation. It fails to explain what a 'machine-ready call plan' is, how matching works, what the parameters do, or what the response contains. This is insufficient for an agent to use the tool effectively, especially with three sibling tools present.

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 by explaining what 'query' and 'input' mean. It does not mention either parameter, nor does it provide any context about how they are used. With no parameter information in the description, an agent cannot understand what to pass, making this dimension critically weak.

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 clear purpose: return a machine-ready call plan for the best matching Qorevia x402 endpoint. It identifies a specific verb ('Return') and resource ('call plan'), and implies a matching function. However, it does not explicitly differentiate from sibling tools like qorevia_find, which might also involve matching, so it is not perfectly distinct.

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 no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or conditions that would steer an agent to a sibling like qorevia_catalog or qorevia_find. The 'best matching' phrase hints at a selection scenario, but it is vague and leaves usage entirely 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, the description carries the behavioral burden. It conveys a read operation returning a single tool definition, but it does not disclose error behavior, not-found handling, or the exact structure of the returned definition.

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 efficient sentence with no filler or redundancy. The core action and lookup mechanism are both 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 one-parameter lookup tool, the description covers the essential operation, resource, and selection method. It is somewhat thin on response content and failure behavior, but overall it provides enough context for an agent to invoke it correctly in most 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 input schema has 0% description coverage, but the parameter is already named pathOrKey, so the description's 'by path or key' largely restates the schema rather than adding new meaning. It does confirm that the parameter is the lookup selector, but no additional format, syntax, or constraints are 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 states a specific verb ('Get') and resource ('one Qorevia tool definition') with a clear lookup mechanism ('by path or key'). It is clear enough to suggest this is a direct single-item retrieval tool rather than a catalog or search tool, though it does not explicitly name its siblings.

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: use this when you already have a path or key and want a single tool definition. It does not provide explicit comparisons or when-not-to-use guidance relative to qorevia_catalog, qorevia_find, or qorevia_route, so the usage signal is only inferred.

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