Interpol

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

Annotations already indicate idempotent and non-destructive. The description adds behavioral context: browser login, token handling, and returning a link with no args. It does not cover error handling, but the safety profile is covered by 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?

Three sentences, each conveying necessary information about setup and usage. There is some redundancy between the 'best' and 'or' alternatives, and phrasing like 'log in in the browser' is awkward, but overall it is efficient and 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 single-optional-param tool with no output schema, the description covers usage scenarios and expected behavior (link). It doesn't specify return values for token-based login, but given the simplicity, this 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?

The description explains the optional token parameter: passing a JWT for session-only login, and no args returns a link. This fully compensates for the 0% schema coverage by giving clear meaning to the 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 purpose: authenticating with MCP.AI for IDE agents via browser login and token. It distinguishes the tool from siblings by describing the specific auth flow, though the verb 'authenticate' is embedded in the name.

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?

Provides explicit usage guidance: permanent connection via config header vs session-only via token parameter, and explains no-args behavior. It doesn't explicitly reference sibling tools as alternatives, but the context is 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavioral detail by specifying distinct output scenarios (authenticated:true vs. connect_url), which helps the agent understand the tool's conditional behavior beyond the annotation safety profile.

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 the primary function, and no redundant wording. Every clause adds useful information without being verbose.

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 params, no output schema), the description fully explains the two possible response states. It is complete for an agent to understand what the tool does and what results to expect.

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 baseline is 4. There is no parameter information needed in the description, and the schema declares an empty properties object, so no additional param semantics are required.

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 opens with a specific verb and resource: 'Returns connection status and URLs.' It clearly distinguishes from sibling tools like authenticate by focusing on status reporting rather than initiating connections.

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 context on what to expect in different states (connected vs. missing credentials), but does not explicitly state when to use this tool versus alternatives. The sibling 'authenticate' implies a contrast, but the description doesn't name it or provide 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 indicate readOnly and non-destructive. The description adds valuable behavioral context: requires prepaid credit ('pague por consulta'), accesses public data only, and includes LGPD data-controller responsibilities. This goes beyond the annotations and helps the agent set user 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 composed of four focused sentences, each serving a purpose: purpose, hosting/payment, data classification, and legal responsibility. It is concise, without redundancy, and front-loads the primary 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 purpose, usage context, payment, data sensitivity, and legal aspects. However, it does not describe the return value or output format, which is notable since there is no output schema. It also leaves the 'completo' parameter unexplained, making the description incomplete for full tool 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 description explicitly lists 'nome, sobrenome e data de nascimento' matching three required parameters, but the 'completo' boolean parameter is not mentioned. It does not provide format details for 'DataNascimento'. Since schema description coverage is 0%, the description only partially compensates for the missing parameter explanations.

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: 'Verifica se um nome consta nas notificações da Interpol' (checks if a name appears in Interpol notifications), specifying the resource (Interpol notifications) and the inputs (nome, sobrenome, data de nascimento). It is easily distinguished from sibling tools, which are unrelated meta-tools.

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?

Provides clear context for when to use: 'para diligência de compliance e AML' (for compliance and AML due diligence). It also sets expectations about no credentials and prepaid credit. However, it does not explicitly mention when not to use it or name alternatives, though no alternatives exist among siblings.

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 adds substantial behavioral context beyond annotations: invoke works one-off even when the MCP is not installed, returns connect links for missing credentials and checkout links for empty wallet payment, writes require workspace owner/admin, and prompt links open without login. It also clarifies the side effects of install vs. invoke. This fully discloses safety, permissions, and state-changing implications.

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 dense single paragraph (~250 words) that packs in a lot of useful information without filler. Each sentence adds value, but the wall-of-text structure makes it harder to scan; bullet points or short sections would improve readability. Given the tool's complexity, the length is justified, but it's not maximally 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?

For a tool with 14 actions, 23 parameters, and no output schema, the description covers the major flows well: search/describe/invoke/install, prompt library operations, auth requirements, and payment/connect handling. However, it omits details on many parameters and doesn't describe return formats beyond saying 'describe returns one MCP's full profile'. The description is strong but not fully complete for an agent to invoke every action correctly without additional 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?

The description mentions the main action enum values and high-level parameter roles (e.g., action=search, describe, invoke, install; tool_id, mcp_id, arguments), but with 23 parameters and 0% schema coverage, it leaves many parameter meanings to inference. For instance, 'immediate', 'tier_slug', 'report_context', 'conversation', and 'prompt_targets' are never explained. The description adds some value but does not compensate for the schema's lack of descriptions.

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 opens with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', clearly identifying both cataloging and execution as the core purpose. It distinguishes this tool from siblings by covering a unique combination of discovery, evaluation, invocation, installation, and prompt-library functions. Even with this breadth, it remains actionable and 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?

The description explicitly maps the core flow (search → describe → invoke) and provides when-to-use guidance for key alternatives, such as 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also distinguishes between the marketplace's search/describe for discovery vs. list_tools for currently callable tools, and explains prompt-library search vs. publish. This is model guidance for choosing among the tool's many actions.

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 idempotentHint=true and destructiveHint=false, so the safety profile is known. The description adds the reproduction context but does not disclose any unexpected side effects or return behavior. It does not contradict annotations, but adds limited 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?

Two sentences: the first states the purpose, the second gives a specific usage instruction. No fluff or redundant wording. Front-loaded with the key 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?

For a simple no-output tool, the description covers the primary action and the key parameter (conversation). However, it does not clarify that the conversation should probably be a JSON-encoded string, nor does it mention the 'context' field. The ambiguity around the conversation format leaves a gap in completeness.

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. It clarifies that 'conversation' should be an array of recent messages for reproduction and implies 'message' is the content of the report. However, it does not explain the 'context' parameter at all, and the schema type for conversation is listed as 'string' while the description calls it an array, creating ambiguity. Partial compensation, but incomplete.

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 'Report' and resource 'bug, missing feature, or send feedback', clearly distinguishing this tool from sibling tools like authenticate or connect. The purpose is immediate and 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 implies when to use the tool: for reporting bugs, missing features, or feedback. It also provides a concrete instruction to include the conversation array for reproduction. Though no explicit alternatives are named, sibling tools are unrelated, so the implied usage is 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?

Annotations already declare readOnlyHint: true, idempotentHint: true, and destructiveHint: false, so the safety profile is fully covered. The description adds no additional behavioral context beyond that, such as what happens if versions are unavailable. It does not contradict annotations, but also provides no extra transparency value.

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 directly states the tool's purpose without any fluff or redundancy. It earns its place entirely and is appropriately front-loaded, making it easy for an agent to quickly grasp the function.

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 parameters, no output schema, and strong annotations—the description fully covers everything an agent needs to know. It clearly states what the tool does, and the annotations handle safety characteristics. There are no missing elements that would impede correct 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 tool has zero parameters, so the schema trivially covers 100% of its parameter definition. Per the rubric, a description of a tool with no parameters can rely on that baseline without needing to compensate for undocumented parameters. No additional parameter semantics 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 tool displays current MCP platform and adapter versions with a specific verb ('show') and resource ('versions'). This unambiguously distinguishes it from sibling tools like authenticate or report_bug, which serve entirely different functions.

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 does not explicitly state when to use this tool or any alternatives. However, the use case is implied by the tool's nature (checking versions), so an agent can reasonably infer when to invoke it. No exclusions or alternative recommendations are 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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable context by specifying the exact data returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations and helps the agent anticipate the output.

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, focused sentence that front-loads the main verb and uses a colon to efficiently list the returned components. Every word adds value; there is no filler or 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?

For a zero-parameter, read-only info tool without an output schema, the description fully explains what the tool returns and is sufficiently detailed for an agent to select and invoke it. There are no missing parameters or behavioral caveats to disclose, and the sibling tools are clearly distinct.

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 zero parameters and empty input schema, the schema covers everything (100%). The description appropriately does not discuss parameters, as there are none. Baseline of 4 is warranted because no additional parameter semantics 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 tool returns the current toolkit state, with a specific verb ('Returns') and a clear resource ('toolkit state'). It enumerates the contents (installed MCPs, connection status, accounts, catalog tool counts), which distinguishes it from siblings like authenticate, connect, and show_version.

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 context (i.e., when you need to inspect toolkit state), but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or direct references to sibling tools. The resource is distinct enough for inference, but explicit guidance is absent.

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