MPT SP Campinas: Certidão Negativa de Feitos

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

The description discloses important behavioral details: using the config provides a permanent, non-expiring connection, while pasting gives a session-only login. It also mentions calling with no args returns a link. These go beyond the annotations, which only state idempotency and non-destructive nature. The side effect of modifying config is implied and addressed.

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 lengthy and rambling, mixing instructions, best practices, and alternatives in a single block. It lacks clear structure (e.g., bullets or steps) and could be shortened significantly while retaining key information. The phrasing 'log in in the browser' is awkward and repetitive.

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 authentication context, the description covers all necessary steps: how to obtain a token, two usage options (config vs. session), and behavior when no args are provided. It does not mention output schema, but none is defined, so that's acceptable. The description is complete enough for a user to understand the tool's functionality.

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 single parameter 'token' is well explained: providing it uses the token, omitting it returns a link. The description clarifies both usage modes, effectively covering the parameter's semantics despite the schema not having a description. This adds meaningful context beyond the raw 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 as authentication, explaining how to log in and obtain a token. It distinguishes itself by focusing on the token retrieval and usage, which is specific enough. However, the phrase 'MCP.AI for IDE agents' is somewhat vague and could be clearer.

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 instructions on how to use the tool: either add the token to the server config for permanent access or paste it for a session. It implies when to use it (authentication) but does not explicitly mention alternatives or when not to use it. The guidance is present but not comprehensive.

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 readOnlyHint, idempotentHint, and destructiveHint already declared, the description adds genuine value by specifying exact response shapes for different system states (empty pending[], connect_url, per-install URLs). It reinforces the read-only contract without contradicting any 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?

Exactly three sentences, each carrying distinct weight: core function, success condition, and failure/fallback condition. There is zero redundancy. The structure mirrors the tool's internal logic, making it highly scannable and easy to reason about.

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 parameterless, side-effect-free tool with a rich set of annotations and a detailed prose description, this is very complete. The only gap is a potential 'partial connection' edge case that the binary framing ('all connected' vs 'missing credentials') might not fully cover.

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, the baseline is 4. The description wisely communicates that the tool requires no arguments — it derives state itself. The behavioral description of what varies (connection state, URLs) is all the semantic context an agent needs for a 0-arg tool.

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+resource ('Returns connection status and URLs') and enriches it with state-dependent behavior ('When all providers are connected... When credentials are missing...'). The conditional return values clearly distinguish this status-check tool from siblings like 'authenticate' without any ambiguity.

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?

While the description never explicitly names alternatives (e.g., 'use authenticate to initiate'), the clear state-outcome mapping ('returns authenticated:true', 'returns connect_url') implicitly teaches the agent that this is the go-to gor status polling. It provides clear context for when to call this (to check connection state), even if it never explicitly says when *not* to call 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?

Adds key behavioral context beyond annotations: invoke runs uninstalled MCPs one-off without bloating the toolkit, returns connect/checkout links for auth/payment, and writes require owner/admin. No contradiction with readOnlyHint=false or other 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?

Long but well-structured: purpose, core flow, KEY invoke behavior, action distinctions, auth note, prompt library. Every section adds value, though the density and the stray Portuguese example make it slightly less crisp than ideal.

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 the main search/describe/invoke loop, install vs invoke, billing actions, prompt library, and auth requirements. However, it omits the 'resume' action entirely and doesn't clarify several params, which is a gap for a 23-param dispatcher with no output schema.

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 meaning of many action values and core parameters (mcp_id, tool_id, arguments, prompt_slug, prompt_vars) through the flow. However, with 23 params and 0% schema coverage, several params (immediate, tier_slug, conversation, cancel_reason, report_context, request_details, prompt_targets, etc.) are left unexplained. It compensates partially but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is the official mcp.ai marketplace catalog and execution layer, then outlines the search→describe→invoke flow and the prompt library. This strongly differentiates it from sibling tools like authenticate, connect, and toolkit_info.

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

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

It explicitly instructs when to use invoke vs install ('prefer invoke for a single/occasional use'), names list_tools for currently callable tools, subscribe/cancel for billing, request_mcp for new MCPs, and notes owner/admin requirements for writes. This is strong when-to-use guidance.

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 and non-destructive. The description adds significant context: prepaid credit payment, no platform credentials required, official Brazilian sources, data non-confidentiality, and LGPD responsibility. This goes beyond what annotations provide.

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

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

The description is moderately concise, with the main purpose front-loaded. It includes several clauses about hosting, payment, and privacy, but each adds relevant context. It is not overly verbose, though slightly run-on.

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 query tool, it covers payment and data handling, but it omits parameter requirements and expected return behavior. With no output schema provided, the description should explain what the tool expects or returns, making it incomplete.

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 does not explain the cpf and cnpj parameters, their purpose, or whether at least one is required. The input schema shows both as optional, and the description carries no clarification, leaving the agent without essential parameter guidance.

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: querying a Certidão Negativa de Feitos from MPT SP Campinas using the verb 'consulta'. It names the specific resource and is distinct from sibling tools that are platform-level operations (e.g., authenticate, connect).

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 negative certificates and mentions payment, but it does not explicitly state when to use this tool versus alternatives or any exclusions. It lacks clear 'when-to-use' guidance beyond context.

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

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

The description does not contradict annotations (idempotent, non-destructive, non-read-only). It adds the requirement to include conversation for reproduction, but does not disclose what happens upon calling (e.g., creates a ticket, sends an email) or mention idempotency, which is already covered by the idempotentHint 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?

Two concise sentences, front-loaded with the core purpose and a practical instruction. No filler or redundant wording.

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 only 3 parameters and no output schema, the description is adequate but incomplete: it covers the main purpose and flags the key parameter (conversation), but does not define 'message' or 'context', nor describe expected outcomes or error cases. This is acceptable but not comprehensive.

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 explains the 'conversation' parameter (include array with recent messages for reproduction) but does not clarify 'message' or 'context'. This is partial compensation; without describing all parameters, it leaves some 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?

Purpose is clear: 'Report a bug, missing feature, or send feedback' uses a specific verb (report) and resource (bug/feature/feedback). This clearly distinguishes itself from sibling tools like authenticate and show_version, which serve unrelated 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?

Provides context by instructing to include the conversation array with recent messages for reproduction, implying when to use (when reporting bugs/feedback). However, it does not explicitly mention exclusions or alternatives, but given sibling tools are unrelated, this is acceptable.

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 it read-only and idempotent. The description adds that it returns MCP platform and adapter versions, which goes beyond the annotations and clarifies the output. No contradictions.

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?

A single, clear, front-loaded sentence with zero fluff. 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?

For a zero-parameter, no-output-schema version tool, the description is fully complete. No additional behavioral or contextual details are 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?

There are zero parameters and schema coverage is trivially 100%. Per the rubric, a baseline of 4 is appropriate when no params exist, and the description needs no further elaboration.

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 resource ('MCP platform and adapter versions'), making the tool's purpose immediately clear. It distinguishes itself from siblings like 'connect' or 'toolkit_info' by stating exactly what information is returned.

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 clearly implies this is for retrieving version info, and no alternatives need consideration. While it doesn't explicitly name when-not-to-use or alternatives, the context is unambiguous for a version-checking tool.

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 readOnly, idempotent, and non-destructive behavior. The description adds output details but does not elaborate on behavior beyond 'returns state'. It is consistent with annotations, but adds no extra behavioral context beyond what annotations provide.

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

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

The description is a single, concise sentence that directly states what is returned without any unnecessary fluff or redundancy. It is well-structured and immediately understandable.

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?

Since there is no output schema, the description adequately explains the return value by listing the key components (installed MCPs, connection status, accounts, catalog tools). It gives a complete picture of what the caller can 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 input schema has zero parameters and 100% coverage, so the baseline is 3. The description adds no parameter-specific information because there are none to elaborate on. No extra meaning is provided beyond the schema itself.

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 what the tool does: returns the current toolkit state with specific details (installed MCPs, connection status, accounts, catalog tools). This is a specific verb-resource combination that distinguishes it 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 clear context about the tool's purpose (fetching toolkit state) without explicit alternatives. While it does not mention when to use versus other tools, the unique functionality makes the usage implicit. Slight deduction for not explicitly stating exclusions or alternatives.

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