Kudosity

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

Annotations already indicate destructive behavior (destructiveHint: true) and non-read-only status (readOnlyHint: false). The description adds no extra behavioral context, such as side effects on external systems, authentication requirements, or rate limits. It does not contradict annotations, but also does not enrich them.

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 that efficiently conveys the core purpose. It contains no fluff or redundant information, and every word contributes to explaining what the tool does.

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 executes arbitrary API requests, but the description does not mention what the response looks like, error behavior, or potential side effects beyond what annotations hint. Since there is no output schema, the description should at least indicate that a response is returned. The schema covers parameters, but the overall context for an agent is incomplete.

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%, with detailed descriptions for parameters including the HAR request object's subfields (method, url, postData variants, etc.). The tool description itself adds no parameter-specific meaning, but the schema already provides strong semantics, so 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 clearly states the tool's function: 'Executes an API request with a given HAR request object.' This uses a specific verb ('executes') and resource ('API request') and distinguishes it from sibling tools that focus on listing/searching endpoints rather than making actual calls.

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 for executing API requests, but it does not explicitly state when to use it versus alternatives. The only related guidance is in the schema's title parameter, which mentions using 'list-specs' or 'search-endpoints' to see available specs—this is more about parameter resolution than tool 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, indicating a safe read operation. The description adds that the details include 'security schemes and servers', providing useful context about the return content without contradicting the 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?

The description is a single, concise sentence that front-loads the core purpose and key details without any redundant or filler text.

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 tool with fully documented parameters and annotations, the description is adequate. It states what the tool does and what information is included, though it does not describe the return format or potential errors, which is acceptable given the schema and annotations.

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 three parameters (path, method, title), including examples and a pointer to list-specs/search-endpoints. Since schema coverage is 100%, the description adds no further parameter meaning, so the baseline of 3 applies.

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 ('Gets') and the resource ('detailed information about a specific API endpoint'), explicitly mentioning the inclusion of security schemes and servers. This distinguishes it from siblings like list-endpoints (which lists endpoints) and search-endpoints (which searches).

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 when detailed information about a single, known endpoint is needed, but it does not explicitly state when to use this tool over alternatives like list-endpoints or search-endpoints. No exclusions or when-not-to-use guidance is provided.

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 read-only nature is covered. The description adds useful behavioral context (organized by path, results passable to get-endpoint) but does not disclose any limitations such as pagination or output size. It provides some added value beyond annotations but not extensive.

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 concise sentences that front-load the core purpose and then give a practical usage note. Every word earns its place with no redundant information 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?

Given the tool's simplicity (one parameter, no output schema) and existing annotations, the description adequately covers what the tool returns (paths, methods, summaries) and how to use the output. It doesn't mention pagination or error handling, but those are not critical for a straightforward list operation, so it is nearly 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?

The schema has 100% coverage for the single 'title' parameter, including a description that tells users to use list-specs or search-endpoints to see available specs. The tool description itself adds no parameter-specific meaning, so it relies entirely on the schema, which is already complete.

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 ('Lists') and clearly identifies the resource: all API paths with their HTTP methods and summaries, organized by path. It distinguishes itself from siblings like get-endpoint (which fetches a single endpoint) and search-endpoints (which searches), making its 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 indicates a clear workflow: results can be passed directly into get-endpoint, which signals when to use this tool as a discovery step. However, it does not explicitly contrast with search-endpoints or list-specs, so it lacks explicit exclusions, though the context is well implied.

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 indicates this is a safe read operation, and the description is consistent with that. The description adds that it returns 'all' available specs and that the title is the distinguishing field, but it does not disclose return format, ordering, or other behavioral traits. This is adequate given the annotation coverage but not enriched.

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 short sentences, with the primary action stated first. The second sentence adds a practical usage hint without redundancy. Every word earns its place; no fluff or 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?

Given the tool's simplicity (zero parameters, no output schema, read-only operation), the description is sufficiently complete. It states what is listed (all OpenAPI specs) and how to use the result (select by title). No additional context is necessary for an AI agent to understand and 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 tool has zero parameters, so the description is not required to explain parameter semantics. Baseline for zero parameters is 4. The comment about selecting a spec by title hints at the output shape rather than input parameters, which is acceptable since there are no parameters to document.

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 ('Lists') and resource ('all available OpenAPI specs'), making the tool's function immediately clear. It also distinguishes itself from sibling tools like list-endpoints (endpoints vs. specs) and get-endpoint (single endpoint retrieval). The added directive 'Use the title to select a spec' reinforces the 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 usage context is implied rather than explicit: the tool lists all specs so a user can choose one by title. However, there is no explicit statement about when to prefer this over sibling tools, nor any when-not-to-use guidance. This places it at the 'implied usage' level.

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 discloses that the tool always returns a per-operation routing plan with key fields (version, endpoint, auth, example) and that it will ask clarifying questions when information is missing. This adds meaningful context beyond the readOnlyHint and openWorldHint annotations, and there is no contradiction.

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, front-loaded with the purpose, followed by the output format and interaction behavior. Every sentence contributes meaning, with no redundancy or 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?

Given the tool's simplicity (no input schema, no output schema), the description fully covers its purpose, output (routing plan with version, endpoint, auth, example), and behavior (asking clarifying questions). It provides sufficient context for an agent to understand the tool's role among siblings.

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 no parameters, so the baseline is 4. The description does not need to explain parameters, and it does not repeat schema details, which is appropriate for a parameterless tool.

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: determine which Kudosity API version to use per operation. It uses specific verbs and resources ("Determine which Kudosity API version") and distinguishes from siblings like execute-request by focusing on planning rather than execution.

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 on when to use it: when the user wants to know which API version to use for an operation, based on action and auth method. It also instructs to ask clarifying questions if info is missing. However, it does not explicitly name alternative tools or state when not to use it, though the unique focus implies the intended use case.

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 read-only and closed-world behavior. The description adds the valuable context that the search is 'deep' and scans multiple facets (paths, operations, parameters), going beyond simply listing endpoints. It doesn't disclose performance limits, but given the annotations, this is sufficient.

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?

Three concise sentences, each providing unique value: what it does, when to use it, and how results connect to 'get-endpoint.' 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 one-parameter search tool with read-only annotations, the description covers purpose, usage, and a concrete next step. It would be slightly stronger if it hinted at result format or size, but the mention of passing results to 'get-endpoint' implies compatibility, which is adequate.

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 a single parameter 'pattern' clearly described as case-insensitive. The description adds no new param semantics beyond calling it 'keywords,' so it stays at the baseline 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 uses a specific verb ('deep search') and clearly identifies the resource ('API endpoints') and the scope ('paths, operations, and parameters'). It distinguishes itself from sibling tools like 'list-endpoints' by emphasizing search across multiple dimensions.

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?

Explicitly states when to use: 'to find specific API capabilities, required parameters, or data models based on search keywords.' While it doesn't list alternatives or when-not-to-use, the use case is clear and it suggests a direct workflow with 'get-endpoint.'

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