SEFAZ SP: Cadin

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

The description discloses behavioral traits beyond annotations, such as the two modes (permanent vs session-only) and that calling with no args returns a link. It does not contradict the annotations (readOnlyHint=false, idempotentHint=true) and adds practical context about the effects of different calls.

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 concise, with three sentences covering purpose, best practice, and alternative. It is well-structured and front-loaded, with no unnecessary 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 the simplicity of the tool (one optional param, no output schema), the description is complete. It explains the two invocation modes and the expected behavior. It does not describe the returned link's format, but that is not critical for 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 schema has a single optional 'token' parameter with no description. The description compensates by explaining that providing a token triggers a session login, and omitting it generates a link. This adds meaning beyond the schema's empty description.

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 authenticate IDE agents by logging in and obtaining an access token. It specifies the action (log in) and the resource (the server), but does not explicitly differentiate it from the sibling 'connect' tool, making it slightly less than perfect.

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 scenarios: adding the token to config for a permanent connection, or pasting it for a session-only login, and calling with no args to get the link. It does not mention when to use this over the sibling 'connect', but gives clear context for its own 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 read-only, idempotent, and non-destructive behavior. The description adds valuable conditional detail about the response shape (authenticated:true, empty pending[], connect_url, per-install URLs), going beyond the basic 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 main purpose, and no unnecessary wording. Every clause earns its place by explaining a distinct outcome.

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?

With no output schema, the description covers the main return states (all connected vs. missing credentials) and the key fields (authenticated, pending, connect_url). It could mention partial-connection edge cases, but the tool is simple and the description is largely sufficient.

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 parameter-level guidance is not needed. Per the rubric, 0 params receives a baseline of 4, and the description appropriately focuses on behavior rather than inputs.

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 ('Returns') and clearly identifies the resource (connection status and URLs). It is distinct from siblings like authenticate or show_version, though it does not explicitly contrast itself 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 provides conditional context ('When all providers are connected... When credentials are missing...') that implies when the tool is useful, but it does not explicitly say when to use this tool versus alternatives like authenticate. Usage is implied rather than stated.

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 (readOnlyHint=false, destructiveHint=false), the description adds essential behavioral context: it discloses that invoke executes even without installation, returns a connect link for auth, and returns a checkout/top-up link for payment. It explicitly states that writes (install, subscribe, cancel, and the install behind invoke) require owner/admin permissions. It also clarifies the distinction between running a tool and installing it into the toolkit. No contradictions with 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 dense paragraph but is front-loaded with the purpose and core flow. It uses arrows and explicit action names to structure the mental model. While lengthy, it avoids fluff and packs essential distinctions (installed vs. invoked, payment links, prompt publishing). It could be broken into bullets for scannability, but the logical flow is clear and efficient.

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?

With no output schema and 23 parameters, the description compensates by explaining the main action enum in detail (search, describe, install, invoke, prompt actions), the execution model (invoke works without installation, returns auth/payment links), permission requirements ('Writes require workspace owner/admin'), and the prompt-sharing feature. It covers edge cases like credential needs and payment failures. This gives the agent enough context to decide when and how to use 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?

Schema coverage is 0%, so the description must compensate. It explains the critical 'action' parameter in detail (all 14 enum values are described through the workflow), and clarifies key identifiers like 'tool_id' and 'mcp_id' (though not by name, but by context). It does not individually document all 23 parameters (e.g., 'limit', 'tier_slug', 'cancel_reason'), but the description provides enough context for an agent to infer type and purpose from the action-specific explanations. This exceeds minimal compensation but doesn't enumerate every parameter explicitly.

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 identifies the marketplace as 'the official mcp.ai marketplace' and details its dual role: cataloging MCPs/tools and executing actions via 'action' parameter. It clearly enumerates the distinct capabilities (search, describe, invoke, install, subscribe, etc.) and differentiates from sibling tools like 'connect' or 'toolkit_info' by framing itself as the central catalog and execution engine. The verb and resource are specific 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?

Provides explicit guidance on when to use each action: 'search → describe → invoke' core flow, and explicitly states 'prefer invoke for a single/one-off' vs 'Use install to make an MCP PERMANENT'. It also differentiates between the marketplace's prompt functions ('search_prompts', 'get_prompt', 'publish_prompt') and MCP operations. Mentions permission requirements for write actions, and explains when links (connect, checkout) are returned. This is model-level 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 indicate idempotentHint=true and destructiveHint=false, which are already provided. The description adds that the conversation array should be included for reproduction, which is a behavioral detail beyond annotations. However, it doesn't disclose what happens after reporting (e.g., whether it creates a ticket, sends an email) or any side effects. With annotations covering safety, a 3 is appropriate.

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 concise, two sentences, and front-loaded with the purpose. It includes a key usage hint about the conversation array. No wasted words, but it could be slightly more structured with parameter details.

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 3 parameters with 0% schema coverage and no output schema, the description is insufficient. It doesn't explain the 'context' parameter, the format of 'message', or what the response will be. The conversation parameter is mentioned but not fully specified. For a reporting tool, more detail on expected input and outcome 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?

Schema description coverage is 0%, so the description must compensate. It mentions 'conversation array' but the schema defines 'conversation' as a string with default '[]', which is ambiguous. The description doesn't explain the 'context' parameter or the format of 'message'. It adds minimal value beyond the schema, and the conversation parameter is only partially explained.

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: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and resource ('bug'), and distinguishes from siblings by covering feedback and feature requests. However, it doesn't explicitly differentiate from other tools like 'connect' or 'marketplace', but the purpose is clear enough.

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 (when reporting bugs, missing features, or feedback) but does not explicitly state when not to use it or mention alternatives. It provides a hint about including the conversation array for reproduction, which is useful context, but lacks explicit exclusions or alternative tool references.

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, idempotent, and non-destructive. The description adds meaningful context about the data source, LGPD compliance, and the fact that data is not confidential, going 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 concise and front-loaded with the tool's purpose. It packs useful information into three sentences, though the LGPD clause is somewhat dense and could be simplified.

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 consult tool, the description covers the main aspects (what, source, payment, data governance). However, it lacks details about the return format, possible error conditions, and parameter usage, which are not supplied by an output schema or parameter descriptions.

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 0% description coverage and the description does not explain the parameters (cpf, cnpj, nome). Although the names are self-evident, the description fails to add any nuance about querying by these fields, required combinations, or formatting.

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 performs a consulta (query) to Cadin from SEFAZ SP, using an official source. It distinguishes itself from sibling tools (authenticate, connect, etc.) by specifying its resource and action.

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 useful usage context (no platform credentials, prepaid credit per query), but it does not explicitly state when to choose this tool over alternatives or provide exclusion criteria. The intended use case is implied rather than directly articulated.

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 idempotentHint=true, and the description's 'Show' wording is consistent. It adds the detail that both MCP platform and adapter versions are returned, which is useful but not entirely necessary given the simple nature of the 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?

A single, front-loaded sentence delivers the exact purpose with no 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 version-listing tool with no parameters and no output schema, the description is sufficiently complete. It could have mentioned the lack of side effects or the fact that it's safe to call anytime, but given the tool's simplicity, this level is adequate.

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 parameters and 100% schema coverage, the baseline is 4. The description correctly implies a parameterless call, and no additional 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 clearly states the tool 'Show the current MCP platform and adapter versions.' It uses a specific verb (Show) and a specific resource (MCP platform and adapter versions), and it is distinct from sibling tools like 'connect' or 'authenticate'.

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 is provided on when to use this tool versus alternatives such as 'toolkit_info' or 'marketplace'. There is no mention of exclusions, prerequisites, or typical use cases, so the agent receives no comparative 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint as false. The description adds valuable context beyond annotations by specifying exactly what information is returned (installed MCPs, connection status, accounts, and tool exposure counts), which helps infer the read-only nature and outputs. It doesn't mention any rate limits or caveats, but given the annotation coverage, this 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 is entirely informative, with no filler or redundancy. It clearly enumerates the key information without any wasted words, making it both concise and structured.

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 this is a simple status-report tool with no parameters and no output schema, the description fully covers the expected return content (all elements are listed). It also aligns with the annotations. There is no missing context that would hinder an agent's understanding.

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 confirms this (100% schema description coverage). No parameters means the description doesn't need to elaborate on them. Baseline for zero parameters is 4, and the description doesn't add unnecessary param information.

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 'Returns' and clearly specifies the resource ('current toolkit state') and includes a detailed list of what that state comprises (installed MCPs, connection status, accounts, and tool counts). This clearly distinguishes it from sibling tools like 'authenticate' or 'connect' which serve 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 implicitly conveys that this tool is for inspecting toolkit state rather than modifying it. It doesn't explicitly compare with alternatives like 'show_version' or 'marketplace', but the content makes it clear it's for status queries. The absence of explicit 'use this when...' statements is a minor gap, hence 4.

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