Prefeitura PE Recife: CPOM

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

The description discloses important behavior beyond annotations: it explains permanent vs session-only login mechanisms, and that calling with no args returns a link. It does not contradict the idempotentHint annotation. It could further mention the invocation response format, but the core auth behavior is transparent.

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 moderately long but front-loads the purpose and covers login flow, token format, and an alternative setup in a concise way. The reference to 'MCP.AI' as a platform/organization is the opening and adds a little context, but does not waste much space.

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 and one optional parameter, the description adequately covers flow, input format, and outcome ('get the link'). It could mention the output shape or failure conditions, but it is largely self-contained for selecting and invoking the 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?

The schema only lists 'token' as a string with no description, and schema description coverage is 0%. However, the description fully compensates by explaining what to pass: { token: '<jwt>' } for session login, and no args for obtaining the link. This adds the necessary semantic meaning for the single 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 identifies the tool as an authentication flow: it logs in in the browser, provides an access token, or accepts a pasted token. It distinguishes its behavior by explaining invitation/credential handling, but it does not explicitly contrast with sibling 'connect' or others, so it lacks full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit invocation guidance: call with no args to get the link, or call with { token: '<jwt>' } after the user pastes. It also suggests a permanent alternative via server config, which acts as a conditional 'when not to use this tool' instruction, though it does not mention all sibling 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds behavioral context by detailing return values for both connected and missing-credential states, including the authenticated flag, pending array, and URLs, which goes beyond the annotations without contradicting 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 two concise sentences. The first sentence front-loads the primary purpose, and the second clarifies outcomes for key scenarios. Every word adds value, with no redundancy 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?

For a zero-parameter status tool, the description covers the essential return scenarios (connected and missing credentials) with specific field names, making it complete enough to guide usage even without an output schema. Sibling context like 'authenticate' highlights its role in checking pre-auth state.

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. The description does not need to explain parameters, and it thoroughly describes behavior and outputs since no input is 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 clearly states the tool "Returns connection status and URLs," which identifies both the action and the resource. This differentiates it from sibling tools like "authenticate" (which likely initiates connections) and "toolkit_info" (general information).

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 for checking connection state, and the scenarios described (all connected vs. missing credentials) give context. However, there is no explicit statement about when to use it instead of alternatives like 'authenticate' or when not to use it.

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 goes far beyond annotations to explain behaviors: invoke runs even when MCP is not installed, returns connect/checkout links for auth/payment, writes require owner/admin, and search/describe flag installed status. No contradiction with readOnlyHint=false, openWorldHint=true, etc. Provides extensive context on side effects and prerequisites.

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 that packs a lot of information but is hard to scan. Every sentence adds value, but lack of formatting (bullets, line breaks) reduces readability. It is verbose but efficient; still, it could be restructured for better clarity without losing content.

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 is very thorough for a complex tool: covers flow, permissions, error handling (connect/checkout links), install vs invoke trade-offs, and the prompt library. However, it omits details on many parameters and does not specify return formats for actions, but given no output schema and multiple actions, it is largely complete. Only minor gaps in exact parameter usage keep it from a 5.

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 0% schema description coverage and 23 parameters, the description must compensate. It explains the meaning of key parameters (action, mcp_id, tool_id, arguments) implicitly through the flow, but leaves many (limit, query, immediate, tier_slug, prompt_*) unexplained. It provides some value but does not fully cover parameter semantics, falling short of the burden.

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 identifies this as the official mcp.ai marketplace, covering both discovery and execution of MCPs, plus a prompt library. It distinguishes from siblings like authenticate or connect by focusing on catalog, running, installing, and billing. The verb+resource+scope is very specific and covers all actions.

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: a core flow (search → describe → invoke), clear distinction between invoke (one-off, no installation) vs install (permanent), and when to use search_prompts/get_prompt/publish_prompt. It also mentions requiring workspace owner/admin for writes, and lists alternatives for features like report_bug and request_mcp.

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 the annotations (readOnly, idempotent), the description discloses that the tool is hosted by the platform, requires prepaid credit, does not need platform credentials, returns only non-confidential data, and is subject to LGPD compliance. These behavioral and contextual details add significant 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 succinct, covering the essential points in three sentences without redundancy. Front-loads the purpose, then provides relevant operational and legal context. Every phrase earns its place.

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 query tool with one parameter and no output schema, the description covers key aspects: purpose, pricing model, data source, confidentiality, and legal responsibility. However, it omits any information about the response format or typical use cases, and does not explain the acronym CPOM, which could be unclear to some agents.

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 a single required parameter 'cnpj' with no description, and the schema description coverage is 0%. The tool description does not mention or explain the 'cnpj' parameter at all, leaving agents to infer its purpose from the parameter name alone. The description fails to compensate for the lack of schema documentation.

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 the specific verb 'consulta' (query) and clearly identifies the resource as CPOM data from official Brazilian sources. It distinguishes itself from generic sibling tools (authenticate, connect, etc.) by indicating its domain-specific purpose, though it does not explicitly contrast with them.

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 by mentioning payment per query and lack of platform credentials, but it does not explicitly state when to use this tool over alternatives or provide exclusions. No named alternatives or scenarios are given.

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 it's not read-only, not destructive, and idempotent. The description adds context about including conversation data for reproduction but does not disclose what happens after submission (e.g., where the report goes, any side effects). It adds some value beyond annotations but lacks behavioral specifics like confirmation or storage.

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 concise sentences, front-loaded with the tool's purpose and immediate usage instruction. 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 feedback tool with no output schema and minimal annotations, the description covers what it does and how to use it. It lacks detail on post-submission behavior or parameter specifics, but given the low complexity, it is reasonably 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?

Schema coverage is 0%, so the description must compensate. It clarifies the purpose of the 'conversation' parameter (recent messages for reproduction) but leaves 'context' and 'message' vague. The description's mention of 'conversation array' conflicts slightly with the schema's string type, but that is a schema issue. Marginal value added.

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's purpose: report a bug, missing feature, or send feedback. The verb 'report' and noun 'bug/feature/feedback' are specific and distinct from sibling tools like authenticate or show_version, which have 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?

Description gives usage context by instructing to include the conversation array for reproduction, which implies when to use (when reporting issues). It does not explicitly mention alternatives or when-not to use, but no sibling tools overlap in functionality, so the guidance 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?

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds no contradictory information and is consistent with these traits, but it also does not elaborate on any side effects or limitations, which is acceptable given the annotations cover the main behavioral aspects.

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 contains only essential information. It avoids any redundancy or unnecessary elaboration, adhering to the principle that every word earns its place.

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 and the presence of annotations indicating read-only behavior, the description provides enough context to understand the tool's purpose. It does not describe the output format, but since no output schema exists and the tool is a straightforward version query, this omission is not a significant gap.

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 no parameters, and the schema coverage is trivially 100%. Since there is nothing to explain, the baseline score of 3 applies. The description adds no parameter-related details, but none 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's function: showing the current MCP platform and adapter versions. It uses a specific verb (show) and identifies the resource (versions), making the purpose unambiguous and distinct from sibling 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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention use cases, prerequisites, or scenarios where this tool is preferred, leaving the agent without contextual cues for 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, idempotentHint=true, and destructiveHint=false, so the description does not need to restate these. The description adds value by specifying exactly what information is returned (installed MCPs, connection status, accounts, catalog counts). However, it does not disclose other aspects like latency or that the state might reflect a cached view, but for this simple read-only tool the transparency 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 front-loads the purpose and enumerates the key data points. Every element earns its place: it states the verb (returns), the resource (current toolkit state), and the specific content (installed MCPs, connection status, accounts, catalog counts). There is zero 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?

Given the tool's simplicity (no parameters, no output schema, but clear annotations), the description is fully sufficient. It covers the necessary context: what the tool does and what it returns. A slightly higher score might require an indication of how to interpret the connection status or what 'how many catalog tools' means, but for this scope the description is 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 tool has zero parameters, and schema description coverage is 100% (trivially, as there are no properties). The description clarifies that the tool returns a state overview, which is the only semantic needed. Since no parameters exist, the description fulfills the requirement and adds meaning beyond the empty 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 returns the current toolkit state, listing specific content: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource combination and distinguishes it from siblings like authenticate or connect, which handle actions rather than state inspection.

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 use for checking the current state of the toolkit, but does not explicitly state when to use it versus alternatives like show_version (which likely shows version info) or marketplace (which may list available MCPs). It does not provide exclusions or alternative tool references, but the context is clear enough for a simple informational tool.

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