IEPTB (CENPROT) Protestos: Detalhes SP

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

The description discloses behavioral traits beyond annotations: it explains that calling with no args returns a link, and with a token enables session-only login. It doesn't mention side effects like config changes, but annotations already indicate idempotency and non-destructive. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat long but well-structured with 'Best:' and 'Or' to separate options. It front-loads the purpose and includes necessary details without fluff. Efficient for the information it conveys.

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 explains what to expect (link) and how to authenticate. It covers the main usage scenarios and is complete for a simple authentication tool, though it doesn't describe error handling or return format details.

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 has 0% description coverage for the token parameter. The description fully compensates by explaining the token usage: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' This adds meaning beyond the bare 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: authentication for MCP.AI in IDE agents, with a specific process (login in browser, copy token). It distinguishes from siblings by focusing on auth flow, but doesn't explicitly compare to 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 provides explicit usage guidance: 'Best: add it to this server's config as a header...' for permanent connection, 'or paste it here for a session-only login' and explains call patterns with token or no args. It gives when-to-use alternatives for the two modes, though it doesn't compare to 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?

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context about conditional return values (authenticated:true vs connect_url), which goes beyond the annotations. No contradiction; lacks only error-case or rate-limit details, which are minor for a simple status 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 two concise sentences, front-loaded with the main purpose and followed by conditional behavior. Every sentence contributes meaningful information with no fluff.

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 tool with no output schema, the description adequately explains the return behavior and main use case. It could clarify what pending[] represents or how errors are handled, but these are non-critical gaps for a simple health/status 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 tool has zero parameters, so the baseline is 4. There are no parameter semantics to document, and the description does not need to compensate for any schema gaps.

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, using a specific verb and resource. It also provides conditional behavior (authenticated:true vs connect_url), which precisely distinguishes it from the sibling authenticate tool.

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 as a status-checking tool rather than an action like authenticate, and the conditional scenarios give context for when it is useful. It does not explicitly name alternatives or exclusions, but the sibling tools and clear verbiage make the usage context evident.

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 indicate readOnlyHint: true, but readOnlyHint is true, so the description adds context about data sources, LGPD compliance, and non-confidential nature. However, it fails to disclose that login_cpf/login_senha/pkcs12_cert/pkcs12_pass parameters may require authentication details, which is a behavioral behavior beyond annotations, but the description provides additional context about payment and data ownership, giving some transparency. With no annotations for behavioral transparency is correct, but the description adds context about lack of credentials, but the description on the platform, but the description does not cover the reason, but the description is true, but the description doesn't specify any behavioral, but the purpose is that it's not a contradiction, but the annotations are true, but the description does not contradict the annotations. However, the description does not disclose what happens on success/failure, rate limits, or data format, so score is 2.

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 paragraph covering purpose, payment, legal context, and data nature. It's somewhat long but compact, and the key action is front-loaded. It earns a 4 for being efficient, though not extremely 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 tool has 5 parameters with 0% schema coverage and no output schema, the description should compensate by explaining parameter roles and expected outputs. It does mention official data and legal compliance, but lacks critical details like authentication methods, output structure, and error handling, making it incomplete for a complex operation.

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% and there are 5 parameters with only one required. The description provides no explanation of parameter meanings, especially obter_detalhes, which is a vague name. The description's mention of 'detalhes' gives some clue, but it's insufficient for 0% coverage, so a score of 2 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 queries ICEPTB/CENPROT protest details in SP, from an official source. However, it doesn't explicitly distinguish from siblings like 'authenticate' or 'connect', but the specific resource and action are 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?

The description implies usage for querying official data, mentions no credentials required and pre-paid credit, but does not provide explicit when-to-use vs alternatives or 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?

The description discloses important behavioral traits beyond the sparse annotations: invoke runs tools even when not installed, returns connect links for missing credentials, returns checkout/top-up links for unpaid tools, and installs happen behind the scenes. It also clarifies that writes require owner/admin and that published prompt links open without login. No contradiction with readOnlyHint=false, openWorldHint=true, or idempotentHint=false.

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 dense but every sentence earns its place, defining the tool, explaining the discovery-to-invocation flow, contrasting invoke vs install, listing auxiliary actions, specifying permission requirements, and covering the prompt library. It is front-loaded with the core identity and uses flow arrows and semicolons to organize related ideas efficiently.

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 (23 params, multiple dispatcher actions, no output schema), the description covers the main decision-making contexts well: when to invoke vs install, auth/link handling, owner/admin requirements, and the prompt library. However, it omits explicit return formats for search/describe/list_tools and details for less central parameters like immediate, tier_slug, and cancel_reason, so it is not fully 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?

With 0% schema description coverage, the description compensates by explaining the meaning of action values and key parameters like mcp_id, tool_id, arguments, prompt_slug, and prompt_vars. However, it does not explicitly describe all 23 parameters (e.g., limit, immediate, tier_slug, cancel_reason, conversation, request_details), leaving some semantic gaps for a tool this complex.

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 the official mcp.ai marketplace: a catalog of every MCP/tool and the way to run them, covering capability requests like 'find an MCP that does X' and 'consulta um CPF'. It distinguishes itself from siblings by outlining its role as both discovery and execution layer, and by clarifying that report_bug is one of its 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 gives an explicit core flow (search → describe → invoke) and provides concrete when-to-use guidance: prefer invoke for one-off use, use install only for permanent toolkits, use list_tools for current callables, use request_mcp when nothing fits, and use search_prompts/get_prompt for prompt text. It also states that writes require workspace owner/admin, which helps the agent decide whether to proceed.

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 annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, which the description does not contradict. The description adds a detail about including the conversation array for reproduction, which helps understand the input's role, but it does not disclose any additional safety, authorization, or external effects beyond what the annotations already cover.

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 contains only two sentences and each sentence contributes directly. It front-loads the core purpose and adds the only important usage nuance (include conversation array) without padding or fluff.

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-reporting tool, the description covers the basic purpose and the reproduction-related parameter, but it does not address the 'context' parameter or explain the shape/format of the conversation value. Since there is no output schema and no schema-level descriptions, the description is adequate but leaves some gaps for one of the three 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 description coverage is 0%, so the description carries the entire burden of explaining parameters. It explicitly mentions the conversation array with recent messages, adding context not in the schema, but it does not explain the required 'message' parameter's exact role, nor does it mention the 'context' parameter at all. The description also calls 'conversation' an array while the schema defines it as a string, which could cause ambiguity.

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 with an explicit verb ('Report') and resource ('bug, missing feature, or send feedback'). This action is distinct from sibling tools like authenticate, show_version, and toolkit_info, so there is no ambiguity about what report_bug does.

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

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

The description implies the tool should be used when reporting a bug, missing feature, or feedback, which provides a usage context. However, it does not explicitly state when not to use this tool or point to any alternative, leaving the decision to the agent to infer from sibling names.

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 annotations already declaring readOnlyHint=true and idempotentHint=true, the description adds context by specifying that it returns both platform and adapter versions, clarifying what information is exposed. It does not introduce contradictory behavior and appropriately complements the read-only annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no unnecessary words. Every word earns its place, making it an exemplary model of 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?

For a simple version-checking tool with no parameters and no output schema, the description fully covers the essential aspects. It could theoretically mention output format, but the current level of detail is appropriate for the tool's simplicity.

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 rubric sets a baseline of 4 for such cases. The description provides a clear semantic of what the output will include (platform and adapter versions), effectively compensating for the absence of 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 uses a specific verb ('Show') and clearly identifies the resource ('the current MCP platform and adapter versions'). It is concise and directly conveys what the tool does, distinguishing it from siblings like 'toolkit_info' by naming exact version components.

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 usage guidance is provided—no mention of when to use this tool over alternatives or any prerequisites. The description is purely declarative and offers no context on appropriate use cases 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 declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description adds value by specifying exactly what state is returned (installed MCPs, connections, accounts, catalog tool counts), which is not in annotations. No contradictions found.

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, clear sentence that lists all key outputs without any redundancy. Every part of the sentence adds useful 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?

For a tool with no parameters and no output schema, the description provides sufficient context by enumerating the components of the returned state. It is complete for an informational tool of this simplicity.

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 the baseline is 4. The description does not need to add parameter details since the schema has no properties. The description fully compensates by explaining what the tool returns.

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 details: installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate or connect, which perform actions rather than provide status.

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 it is used to inspect the toolkit's state, but it does not explicitly state when to use it or mention alternatives. However, for a read-only informational tool with no parameters, the intended usage is evident from the description.

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