Zyla API Hub

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

No annotations provided, so description carries full burden. It notes the auth requirement (API key in header) and implies read-only access. Does not disclose rate limits or potential side effects.

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, front-loaded with purpose, no redundant information. Efficient and clear.

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 no parameters and no output schema, the description fully explains tool behavior, return values, and use case. Complete for a simple read-only 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?

No parameters exist, so baseline is 4. Description adds value by detailing what is returned, compensating for lack of output 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?

Description clearly states the tool checks account status, billing, and usage, listing specific returns (plan info, API call count, credit card, payments). Distinguished from siblings by focusing on billing issues rather than catalog or API info.

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 says to use for diagnosing blocked API calls due to missing card or failed payment. Mentions requirement for API key in Authorization header, but lacks mention of when not to use.

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 states the tool returns paginated results with total count and page info, but does not disclose authentication requirements, rate limits, or that it is read-only. The description adds some behavioral context but is not comprehensive.

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 concise sentences that front-load the core purpose and key features. Every sentence provides valuable information with no 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 the tool has 6 parameters and no output schema or annotations, the description covers pagination, filtering, and response contents. It is mostly complete but could mention authentication or error cases for full context.

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 description reinforces that search is server-side across all APIs and mentions filtering, but does not add significant new meaning 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 it's for browsing the full Zyla API Hub catalog with pagination. It distinguishes from sibling tools like 'search_catalog' by emphasizing exploration of all public APIs beyond the top 500, 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 advises using this to explore all public APIs beyond the top 500, which sets context. However, it does not explicitly contrast with the sibling 'search_catalog' tool or specify when not to use it, lacking explicit alternatives.

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 fully covers behavioral traits: it requires user API key and credit card, explains pay-per-successful-request billing, mentions that charges appear at billing cycle end, and describes the 402 error recovery process. No contradictions exist, and this level of detail exceeds expectations.

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 efficiently composed of four sentences, each adding value (purpose, prerequisites, billing, error handling, parameter listing). It is front-loaded with the core action and lacks fluff, though a slight reduction in redundant parameter mention could improve conciseness.

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 complexity (4 parameters, billing dependency, error handling) and no output schema, the description is highly complete. It covers the billing model, error recovery, and how to discover prices. It does not describe the response format, but since the output is the API's response, this omission is acceptable.

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 baseline is 3. The description adds 'Pass the api_id, endpoint_id, HTTP method, and parameters,' but this merely restates the schema properties. No additional meaning beyond the schema is provided, so it scores at 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 'Call an API endpoint on Zyla API Hub,' using a specific verb and resource. It distinguishes itself from sibling tools by explicitly recommending get_api_info for price checking, making the purpose unambiguous and differentiated.

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 explicit guidance on when to use the tool (to call an API endpoint) and when not to (by suggesting get_api_info for price checks). It also details prerequisites (API key, credit card on file), billing model, and error handling steps for 402 errors, offering comprehensive usage context.

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 transparently describes the return data (name, description, category, pricing per call, endpoints with parameters, pricing, examples). No side effects or behavioral issues are mentioned, but as a read-only operation, this is adequate.

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 sentence that is moderately concise, efficiently conveying purpose and return structure without unnecessary words. It could be slightly improved by splitting, but is 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?

Given there is no output schema, the description thoroughly lists what is returned (name, description, category, pricing per call, endpoints with parameters, pricing, and example values). This is complete and leaves no ambiguity about the output.

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 provides 100% coverage with a description for api_id. The description reinforces that the ID is numeric and gives an example value (781), adding clarity beyond 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 clearly states it retrieves full details of a specific API by numeric ID, listing specific return fields (name, description, category, pricing, endpoints). This distinguishes it from siblings like browse_catalog or search_catalog, which are for browsing or searching.

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 needing detailed info on a known API by ID. It doesn't explicitly state when not to use it or mention alternatives, but the purpose is clear enough 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?

No annotations are provided, so the description carries full responsibility. It discloses key behavioral traits: the user must open the returned URL, billing is pay-per-successful-request, API calls are blocked without a valid card, and the tool is for adding/updating a card. This is comprehensive and beyond what annotations would typically provide.

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 about 80 words and is front-loaded with the main purpose. Every sentence adds value, covering purpose, required usage, user action, billing, and a prerequisite. It could be slightly more concise (e.g., merging billing sentences), but it remains efficient and 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?

Given no output schema, the description adequately explains the return value (a URL for the user to open) and provides complete context on when to use, billing, and prerequisites. It does not describe the exact response format, but the crucial information is covered, making it sufficiently complete for an agent.

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 100% by default. The description adds no parameter-specific details, but it provides valuable context about the tool's behavior (billing, user action) that goes beyond the empty schema. Baseline for 0 parameters is 4, so this score 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: 'Get a Stripe Checkout URL so the user can add or update their credit card.' It uses specific verbs and resources, and the context signals confirm no parameters. The purpose is unambiguous and distinguishable from siblings like 'account_status' or 'browse_catalog'.

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 states when the tool is required: 'REQUIRED after registration and whenever a 402 error occurs.' It also gives a clear prerequisite: 'Before calling, use get_api_info to check the price per call for each API.' This provides excellent guidance on usage context.

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 full burden. It states that the tool lists categories with counts, which is a safe read operation. It does not disclose any additional behavioral traits like authentication or rate limits, but for a simple list tool this is adequate.

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: first describes the action and result, second provides usage guidance and an example. No wasted words, front-loaded with key 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?

Given zero parameters, no output schema, and a simple purpose, the description is complete. It covers what the tool does and how its output is used, which is sufficient for an agent.

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 no parameters, so baseline is 4. The description adds value by explaining how the output (category names) is used in browse_catalog, though it does not need to describe parameters.

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 verb 'List all available API categories' with specific resource 'categories on Zyla API Hub' and includes the added detail of 'real count of public APIs in each', which distinguishes it from siblings like browse_catalog.

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 instructs to use the returned category names as the 'category' parameter in browse_catalog, providing clear context for when to use this tool. It does not mention when not to use it, but the context is sufficient.

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 fully discloses behavior: returns API key and payment_url, requires user action, explains billing model (pay-per-request, no monthly fees), and states no authentication needed. This is comprehensive for a registration tool.

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 five sentences, each adding value: purpose, return values, required user action, billing model, and authentication. It is front-loaded with the core purpose and is succinct without waste.

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 all essential aspects: purpose, output, user steps, billing, and prerequisites. For a registration tool with no output schema or annotations, it provides complete context for an AI agent to use 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 coverage is 100%, so the description does not need to add parameter details. The description adds no extra meaning beyond the schema, which adequately describes name, email, and password.

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 registers a new Zyla API Hub account, using a specific verb and resource. It distinguishes from sibling tools like account_status or get_payment_url, providing a unique 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 provides explicit instructions: user must open payment_url to add a credit card before making calls. It explains billing and that no authentication is needed, giving clear context for use. It lacks explicit when-not-to-use, but implies it for existing accounts.

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. It discloses caching behavior, automatic fallback, and the return fields (ID, name, description, category, endpoints summary). No mention of authentication or destructive actions, but the tool is a read-oriented 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 three sentences, each providing essential information: verb+resource, behavior, and output. No fluff. The first sentence immediately states the core action.

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 the key behaviors (caching, fallback) and return fields. No output schema exists, but the description compensates. It could mention pagination or rate limits for completeness, but overall it's adequate for a search tool with two parameters.

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 parameters are already well-documented. The description does not add additional meaning beyond the schema (e.g., format constraints, default values). The schema descriptions for 'query' and 'limit' are sufficient.

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 verb 'Search' and the resource 'Zyla API Hub catalog for APIs by keyword'. It distinguishes from siblings like 'browse_catalog' and 'get_api_info' by describing a two-phase search strategy (cached top-500 first, then full server-side).

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 explains that it first searches a cached set and automatically falls back to a full server-side search if insufficient results, giving clear context on behavior. However, it does not explicitly mention when not to use this tool or why a user would choose it over alternatives like 'browse_catalog'.

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