SEFAZ MG: Certidão Negativa de Débitos

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

Annotations already indicate non-read-only, idempotent, non-destructive. Description adds context about auth flow (link generation, session vs permanent) and side effects (modifying config). No contradiction with annotations, and adds useful 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?

The description is a single dense paragraph but avoids fluff. It front-loads purpose and then details two usage modes with 'Best:' and 'Or', which is effective. Slightly long but earns its keep.

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 simple tool (one optional param, no output schema), the description covers invocation modes and outcome (link or session). It doesn't explicitly state return value but implies it. Complete enough for an agent to use correctly.

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%, but the description explains the 'token' parameter's role (JWT for session login) and that omitting it generates a link. This compensates well, though it could explicitly state the parameter is optional.

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 authenticates to MCP.AI via browser login, token acquisition, and configuration. It distinguishes itself from siblings like 'connect' by specifying it's for authentication and providing a detailed workflow.

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 provides explicit when-to-use guidance: for permanent connection add header to config, or for session-only use token parameter or no args to get link. It doesn't explicitly name alternative tools but gives clear usage context, so not a 5.

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 context about the different return states (authenticated vs. pending) which is useful, but does not disclose potential network calls or any side effects beyond what is described, which is acceptable given the read-only nature.

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 highly concise, two sentences that fully capture the purpose and key behavioral details. Every sentence 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?

Given the tool has no parameters and no output schema, the description provides sufficient detail about return values and states. It covers the main use cases (all connected, missing credentials) and is complete for a status-checking tool, though it could mention whether the status is real-time or cached.

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 provides no parameter details. The description fully compensates by explaining the output behavior in different scenarios, making the tool's usage clear without needing parameter documentation. Baseline 4 is appropriate for zero-parameter tools.

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, with specific details about authenticated:true and pending[] when all providers are connected. It distinguishes itself from siblings like authenticate (which likely initiates connections) by focusing on status retrieval, though it doesn't explicitly name 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 implies when to use it: to check connection status and retrieve connect URLs when credentials are missing. It provides clear context on what the tool returns in different scenarios, but does not explicitly state when not to use it or mention alternatives like authenticate.

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?

Even with annotations, the description adds important behavior beyond readOnlyHint/openWorldHint: non-installed invocation runs one-off without bloating the tool list; credential needs return a connect link; empty wallet returns a checkout link; install is permanent; and write actions require owner/admin. No contradiction 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 long but each section earns its place—the core flow is front-loaded, and the detail on one-off invoke vs install provides practical guidance. Faceted formatting would improve skimmability, but for a 23-param multi-action tool the length is reasonably justified.

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 tells what actions return: 'describe returns one MCP's full profile', 'invoke returns a connect or checkout link when needed', and 'publish_prompt saves a prompt and returns a shareable mcp.ai/p/<slug> link.' It does not detail sentinel behavior for every sub-action, but the main flows are sufficiently covered for a tool 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?

With schema_description_coverage = 0% and 23 optional params, the description compensates for the core parameters (action, query, mcp_id, tool_id, prompt_body/prompt_vars) by describing their role in the workflow. However, several parameters such as limit, immediate, conversation, cancel_comment, report_context, request_details, and prompt_targets are never semantically explained; the mass-style description is obliged to fill this gap better.

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 clear purpose: it is the 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates the core flow (search → describe → invoke) and the prompt-library features with specific verbs, distinguishing this umbrella tool from sibling tools like report_bug, toolkit_info, and sefaz_mg_certidao_debitos_consultar.

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 when-to-use advice: 'Use install only to make an MCP PERMANENT', 'prefer invoke for a single/occasional use', 'list_tools lists what is callable right now', and 'subscribe/cancel handle per-MCP billing'. It also distinguishes prompt-library actions (search_prompts/get_prompt/publish_prompt) from MCP/tool actions and notes that writes require workspace owner/admin.

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 readOnlyHint=false and idempotentHint=true, providing some behavioral context. The description adds the useful detail that the conversation array is for reproduction, which helps the agent understand a key input. However, it does not explain side effects (e.g., whether a report is created, sent, or persisted), so transparency is adequate but not rich.

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, front-loaded sentences. The first sentence states the action and targets, and the second gives a specific instruction. No filler or redundant 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 simple bug-reporting tool with no output schema, the description covers the action and the key reproduction input. However, the gap in parameter semantics (especially the mismatch between 'conversation array' and the string schema type) means an agent might craft incorrect inputs. The overall context is adequate but missing clarity on message and context 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 must carry the parameter semantics burden. It only mentions the conversation parameter, and even then calls it an 'array' while the schema defines it as a string (possibly a JSON string). It does not explain the required 'message' parameter or the optional 'context' parameter, leaving significant 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 uses a specific verb ('Report') and identifies the resource ('a bug, missing feature, or send feedback'). It clearly distinguishes from sibling tools like authenticate or show_version, which have no overlap with bug reporting.

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 states when to use the tool ('Report a bug, missing feature, or send feedback') and gives direct guidance on what to include ('Include the conversation array with recent messages for reproduction'). No exclusions or alternatives are provided, but siblings are unrelated, so usage context is effective.

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. The description adds valuable context beyond annotations: the query is official and citizen-accessible, paid per consultation via prepaid credit, does not use platform credentials, and involves LGPD data-control responsibilities. No contradiction 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 main purpose is front-loaded in the first sentence, and subsequent sentences add useful context about cost, credentials, data sensitivity, and LGPD. Slight redundancy exists between 'fonte oficial' and 'fontes e órgãos oficiais brasileiros', but overall the description is compact and readable.

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 7 parameters and no output schema, the description is incomplete. It does not explain what the consulted certificate looks like, what return format the agent can expect, nor how the various login and PKCS#12 parameters should be supplied or chosen. Annotations cover safety traits, but operational completeness is lacking.

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 7 parameters with 0% description coverage, and the description provides no per-parameter guidance. Parameter names like cpf, cnpj, ie, login_cpf, login_senha, pkcs12_cert, and pkcs12_pass are somewhat self-explanatory, but the description does not clarify which identifiers are required, whether credential parameters are alternatives or complements, or expected formats.

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 specific resource ('Certidão Negativa de Débitos' from SEFAZ MG) and the operation ('consulta em fonte oficial'). This clearly distinguishes the tool from unrelated siblings such as authenticate, marketplace, and report_bug.

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 for use: it queries official Brazilian sources, requires prepaid credit rather than platform credentials, and concerns non-confidential data. It does not explicitly list exclusions or alternatives, but the use case is made apparent and context-rich.

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, which fully cover the safety profile. The description adds no behavioral context beyond the word 'Show,' which aligns with annotations but provides no additional transparency.

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 filler. Every word contributes to explaining the tool's purpose.

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?

This is a trivial no-parameter, read-only version-info tool. The description fully captures what it does, and the annotations cover safety and idempotency. No output schema exists, but the expected return (version strings) is simple enough that omitting its format does not create ambiguity.

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 schema coverage is trivially 100%. Per the rubric, 0 params receives a baseline of 4; no additional parameter documentation is necessary.

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 a precise resource ('current MCP platform and adapter versions'), clearly distinguishing this from siblings like toolkit_info or report_bug. It unambiguously identifies what the tool 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 usage when version information is needed, but provides no explicit when-to-use or alternative-based guidance. For such a simple tool this is acceptable, but it does not explicitly exclude or contrast with 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 disclose readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so this is known as a safe, non-destructive read. The description adds value by specifying exactly what state is returned: installed MCPs, connection status, accounts, and catalog-tool counts. There is no contradiction with the 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, front-loaded sentence that starts with the action and then efficiently enumerates the exact return categories. Every phrase earns its place, with no filler, repetition, or unnecessary detail.

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 low complexity (zero parameters), the strong annotations, and the absence of an output schema, the description provides a solid, complete overview of what the caller will learn. It could be slightly richer by mentioning whether the state is a live snapshot versus a cached summary, but that is a minor 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?

This tool has zero parameters, so there is no parameter semantic burden on the description. The schema already covers everything by defining an empty object. The description appropriately indicates that no input is needed and instead focuses on output scope.

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 and object: "Returns the current toolkit state" and then lists what that includes — installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like show_version or report_bug by scoping it to toolkit/connectivity state.

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 for inspecting the current toolkit/connection state, which is a clear context. However, it does not explicitly state when to prefer this over sibling tools such as show_version or authenticate, nor does it give any when-not-to-use guidance.

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