Apiosk MCP

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

Beyond the annotations (readOnlyHint, idempotentHint, openWorldHint, destructiveHint), the description adds critical behavioral context: it explains that results contain an 'executable_via' field indicating whether to call apiosk_execute or apiosk_inspect_x402 + apiosk_fetch_paid, and that discovery never spends automatically. This fully clarifies the tool's behavior and safe usage.

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 exceptionally concise—two sentences that front-load the core purpose, then provide usage differentiation and behavioral notes. Every sentence adds essential information without redundancy, achieving maximum efficiency.

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 (6 parameters, output schema, multiple siblings), the description covers all key aspects: purpose, when to use, decomposition pattern, return format (executable_via), and safety assurances. The output schema supplements return details, so no gaps remain.

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?

With 100% schema description coverage, the baseline is 3. The description adds value by linking the 'segments' parameter to the decomposition pattern and explaining the role of 'sources' (e.g., 'wellknown' requires explicit probe_hosts). This contextual guidance elevates the score above baseline, though not to a 5 since the schema already documents all 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 tool's purpose: 'Find the best paid x402 API for a data capability across discovery sources.' It includes specific verbs ('Find', 'Decompose', 'call'), identifies the resource ('paid x402 API'), and explicitly distinguishes it from sibling tool apiosk_search: 'Use this instead of apiosk_search when the goal is get real paid data for X, not just browsing.'

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 this tool ('when the goal is get real paid data for X') versus the sibling apiosk_search. It also instructs to 'Decompose the user's request into capability segments first, then call this once per capability.' Additionally, it clarifies that discovery never spends automatically, setting expectations for safe usage.

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 destructiveHint=true, so the tool can be destructive, but the description does not elaborate on this or other behavioral traits like side effects, authentication needs, or rate limits. It merely repeats the execute contract, adding minimal value beyond 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 captures the core functionality without unnecessary words. It could be slightly expanded to include important caveats, but as a concise statement it is effective.

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 (5 parameters, output schema, destructive annotations), the description is somewhat incomplete. It does not mention the nature of the /execute contract, potential side effects, or error handling. The output schema exists but is not referenced. The description is adequate for a basic understanding but lacks completeness for safe usage.

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 100% description coverage for all 5 parameters, so the schema itself provides adequate semantics. The tool description adds no additional meaning for parameters, which is acceptable given high coverage, but also doesn't highlight any critical points.

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 any Apiosk API by slug. The verb 'execute' and resource 'Apiosk API' are specific, and it distinguishes from sibling tools like apiosk_get_api or apiosk_search which have different purposes.

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 when to use this tool (to execute an API by slug) but does not provide explicit guidance on when not to use it or how it compares to alternatives like apiosk_get_api or apiosk_explore. Usage context is only indirectly understood.

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 destructiveHint=false, so the description need not repeat safety. It adds context that the tool explores 'one group at a time', implying a browsing pattern, but lacks details on pagination, rate limits, or auth. With annotations covering safety, a score of 3 is fair as it adds some but not extensive behavioral context.

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 fluff. It is front-loaded with the core action. However, it could add a bit more detail without becoming verbose, hence 4.

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 6 parameters and an output schema. The output schema covers return structure, so the description need not explain that. However, the description fails to clarify how parameters like sort, limit, order, offset, and listing_type affect browsing behavior. For a browse tool with multiple configuration options, this lack of contextual guidance makes it incomplete, earning a 3.

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 1 of 6 parameters ('search') has a schema description, giving 17% coverage. The tool description does not compensate by explaining any parameters, leaving the agent to infer meaning from parameter names and enums. For example, 'listing_type' or 'sort' are not described. This is a significant gap for a tool with 6 parameters and low 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 clearly states the tool's purpose: browsing and exploring Apiosk listing groups before narrowing with search. It uses specific verbs 'browse' and 'explore' on the resource 'listing groups', and hints at a sequential workflow that distinguishes it from a direct search tool like apiosk_search, but does not explicitly name alternatives.

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 when to use this tool ('before narrowing with search'), suggesting a preparatory browsing role. However, it does not explicitly exclude scenarios or name alternatives (e.g., apiosk_search for direct search), leaving room for ambiguity.

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?

Adds beyond annotations: gateway enforces per-tx/daily spend limits, only Base+USDC, refuses if live price higher, idempotency key for safe retry. 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?

Single paragraph with front-loaded purpose and usage. Every sentence adds value; no 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?

Covers purpose, usage, prerequisites, behavioral constraints, and parameter hints. Output schema exists, reducing need for return value explanation.

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?

Adds meaning to confirmed_price_usdc (from apiosk_inspect_x402), idempotency_key (safe retry), url (from discovery result). Schemas covered 100% but description enriches further.

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?

Describes paying an external x402 endpoint and returning data, with clear differentiation from apiosk_execute for catalog listings. Verb+resource+scope are specific.

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 use only for external results from apiosk_discover, and for catalog listings use apiosk_execute. Also requires prior call to apiosk_inspect_x402 with user confirmation.

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 provide readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds that it fetches 'full listing detail and agent metadata,' which is somewhat vague but non-contradictory. No side effects or behavioral details beyond what annotations imply.

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 of 11 words, with no redundancy or unnecessary information. It is front-loaded and efficiently conveys the tool's purpose.

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 low complexity (one parameter, simple input schema) and presence of an output schema, the description is minimally sufficient. However, it does not clarify what 'full listing detail' entails, which could leave ambiguity for the 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?

The schema covers the single parameter 'slug' with a description and example, achieving 100% coverage. The tool description adds no additional meaning beyond the schema, 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 tool fetches full listing detail and agent metadata for a specific slug, using a strong verb-resource combination. It differentiates from siblings like apiosk_search and apiosk_explore, though not explicitly.

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 on when to use this tool versus alternatives (e.g., apiosk_search, apiosk_explore, apiosk_metadata). The description only states what it does, not context or exclusions.

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 mark this as readOnlyHint=true. The description adds behavioral context by specifying the topics it covers (e.g., auth, payments). No contradictions, and the description provides additional value beyond 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 sentence that efficiently lists the main topics. It is appropriately front-loaded and contains no unnecessary words. Minor improvement could be structuring with bullet points, but it is still concise.

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 presence of an output schema (which covers return value details), the description is complete. It covers the tool's purpose, key topics, and workflow recommendations. No gaps are apparent for this help-oriented 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 the schema already describes the 'topic' parameter thoroughly. The description adds extra context for 'discovery' and 'rails' values, enhancing understanding beyond the 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?

The description clearly states the tool's purpose: to explain Apiosk MCP, covering setup, auth, payments, and workflow. It uses a specific verb 'explain' and distinguishes from sibling action-oriented tools like apiosk_discover, apiosk_execute, etc.

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 the user needs explanations on topics like overview, setup, auth, and payments. It mentions a recommended workflow, which provides context. However, it does not explicitly state when not to use it or list alternatives, though the sibling names make it clear.

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?

Beyond annotations (readOnlyHint, destructiveHint), the description adds that it 'makes one unauthenticated request', 'parses the 402 offer', and is 'Read-only; never spends', disclosing key behavioral traits.

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 focused sentences front-load purpose, then usage guidance and sibling differentiation. No 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?

Given output schema exists, the description covers purpose, usage, and behavioral traits adequately. It could mention edge cases but is complete enough.

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% and parameters are well-documented in the schema. The description does not add extra parameter details but is not required to.

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 explicitly states it 'Read an arbitrary URL's x402 payment terms' and contrasts with sibling apiosk_execute, making the purpose unmistakably clear.

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 provides explicit when-to-use ('Use this on an external result's url from apiosk_discover before paying') and when-not-to-use ('apiosk_execute does not need this'), along with context about the request behavior.

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 this is a read-only, idempotent, non-destructive operation. The description adds context about the user scope and authentication requirement, which supplements the annotations without 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?

Two sentences: first states the core purpose, second states the prerequisite. No unnecessary words. Perfectly 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 zero-parameter list tool with an output schema (not shown but implied), the description provides essential context: user scope and auth requirement. Nothing else is needed.

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 and the schema coverage is 100%, so the description need not explain params. The description implicitly confirms no parameters are needed.

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', the resource 'managed Apiosk wallets', and the user scope 'signed-in user'. This distinguishes it from sibling tools like create, delete, or update wallets.

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 mentions the prerequisite of having an Apiosk dashboard session with appropriate authorization. While it doesn't list when not to use it or alternatives, the context is clear for a list operation.

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 behavioral traits beyond annotations: it states that the output is a buyer guide and a provider guide, tailored to the current auth. Annotations already indicate read-only and non-destructive, so the description adds value by explaining the output structure and tailoring.

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 purpose, followed by parameter guidance. Every sentence adds value with no 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?

For a simple tool with an output schema, the description is complete. It covers the tool's core function, output types, parameter roles, and context. No gaps remain.

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 description adds meaning beyond the input schema: it explains how 'slug' scopes the buyer guidance and how 'role' picks a side. Schema coverage is 100%, and the description enriches the understanding of parameter usage.

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 purpose: to explain how to pay through the Apiosk gateway, providing both a buyer guide and a provider guide. It uses specific verbs and resources ('Explain how to pay') and distinguishes itself from sibling tools (no other tool covers payment guidance).

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 usage context: when you need payment guidance, you can optionally pass a slug to scope the buyer guidance or a role to pick a side. It doesn't explicitly mention when not to use or alternatives, but the context is sufficient for an AI agent to decide.

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 destructiveHint=false, so the safety profile is covered. The description adds context that it's for browsing/filtering but doesn't disclose additional behavioral traits like pagination limits or result structure beyond what's implicit. 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?

Two efficient sentences, no wasted words. The purpose is front-loaded, and the usage guidance is provided in a clear, compact manner.

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 optional params, a full schema, output schema (exists), and good annotations, the description is fairly complete. It covers purpose and usage distinction but doesn't elaborate on pagination or result details, which is acceptable since the output schema handles that.

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 each parameter described. The description adds interpretive meaning, mapping 'by capability' to free-text search and 'price' to sort/order, helping the agent understand how parameters relate to the tool's purpose. This goes 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 the tool searches/browses the Apiosk catalog by capability, price, or category. It explicitly distinguishes from the sibling 'apiosk_discover' by noting that tool is better for fulfilling live data requests, making the purpose specific and well-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: 'When the goal is to fulfil a user request with real paid data... prefer apiosk_discover'. This tells when to use this tool and when to use an alternative, meeting the criteria for high-quality usage guidelines.

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