Conselho Regional de Odontologia PA: Cadastro

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

Annotations already indicate non-read-only, idempotent, non-destructive behavior. The description adds meaningful context: the token expires per session versus a non-expiring config header, and explains how to initiate the flow with or without arguments. 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 longer than typical but every sentence conveys necessary operational detail. It is logically structured: intro, best path, alternative path, and invocation patterns. Minor verbosity, but not wasteful.

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 adequately covers the main behavior: permanent vs session auth, token handling, and no-arg link retrieval. It could mention return values or errors explicitly, but for a simple authentication flow this is 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?

Schema coverage is 0%, but the description fully explains the single optional token parameter: how to pass it, when to use it (after pasting), and what happens when omitted (returns the link). This more than compensates for the sparse 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 function: authenticating with MCP.AI for IDE agents via browser login, token paste, or link retrieval. It uses specific verbs and resources, and differentiates from sibling tools like connect by describing the actual auth flow.

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 usage scenarios: best practice via config header for permanent access, session-only via pasted token, or no-arg call to get the login link. This gives the agent clear decision guidance on which mode 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?

Annotations already declare readOnlyHint and idempotentHint. The description adds value by explaining response behaviors (authenticated:true, empty pending[], connect_url scenarios) that aren't in the annotations. Could add a bit more on partial connectivity, but it's quite 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?

Two concise, front-loaded sentences. The first sentence immediately says what it does, and the second provides condition-based details. 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?

Covers the main success and failure paths (all connected vs missing credentials). With no output schema and simple status behavior, this is nearly complete. Could mention partial connectivity, but it's 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?

No parameters exist; description aligns with baseline 4. It correctly doesn't try to explain what's not there, and since the schema has no properties, there's nothing more to elaborate.

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?

Clearly states 'Returns connection status and URLs' – a specific verb and resource. Describes conditions (all connected vs missing credentials) and differentiates from sibling 'authenticate' by focusing on status rather than the authentication 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?

Gives clear context that this tool is for checking connection status, but doesn't explicitly contrast with siblings like 'authenticate' or state when not to use it. The intended use is implied rather than directly stated, so it stays at a 3.

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 hints. The description adds valuable context: the tool is hosted by the platform, requires payment with prepaid credits, returns non-confidential data, and places data controller responsibility on the client (LGPD). This goes beyond annotations without 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 a single paragraph that covers purpose, payment, data sensitivity, and legal compliance. While it is not excessively long, it includes some legal and payment details that could be condensed, and it lacks clear structuring. It is adequate but not tight.

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 only one parameter, the description should explain what the tool returns and how to use 'inscricao'. It does mention official source and non-confidential data, but omits details about response format, prerequisites, or examples. The incomplete parameter documentation and lack of output info make this insufficient.

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 only parameter 'inscricao' is not explained in the description at all, and schema description coverage is 0%. Since there is no other documentation, the agent cannot infer what value to provide. The description fails to compensate for the missing parameter meaning.

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 consultation (consulta) on official registration data from the Pará Regional Council of Dentistry, using the specific verb 'consultar' and resource 'cadastro'. This is precise and distinguishes it from generic platform tools like 'authenticate' or '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 implies the tool is used for official registration queries, but does not explicitly state when to use it vs alternatives or when not to use it. It mentions payment via prepaid credits and LGPD compliance, which gives some context, but lacks clear usage boundaries.

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?

Provides rich behavioral context beyond annotations: invoke runs one-off WITHOUT adding to toolkit or bloating the list, returns a connect link when credentials are needed and a checkout/top-up link when the wallet is empty, requires workspace owner/admin for writes (install/uninstall/subscribe/cancel and the one-off install behind invoke), and publish_prompt returns a link that opens without login. No contradiction with annotations (readOnlyHint=false aligns with the described writes).

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 ~400-word run-on block with no paragraph breaks or section headers separating the three major areas (MCP discovery/run flow, toolkit management, prompt library). It front-loads the core flow well, but the density and lack of structure make it hard to scan for a specific action. Given the 14-action complexity, length is partially justified, but structured formatting would vastly improve navigability.

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 MCP marketplace half (search/describe/invoke/install flow) is thoroughly and actionably described, covering failure modes, permission requirements, and retry semantics. However, the prompt-library half is under-specified: it names search_prompts/get_prompt/publish_prompt but doesn't map them to their six+ parameters (prompt_body, prompt_vars, prompt_targets, prompt_slug, prompt_category, prompt_description), leaving a substantial portion of the tool surface unclear. With no output schema and 0% schema coverage, this gap matters more.

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 bears the full burden of documenting 23 parameters, but it only explicitly covers the action enum (naming nearly all values) and casually references tool_id, mcp_id, and the prompt actions. Critical params like arguments (JSON string format), prompt_vars, tier_slug, conversation, immediate, cancel_reason/cancel_comment, prompt_targets, and request_details are left unexplained. The agent cannot know how to properly construct an invoke or publish_prompt call from this 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 identifies the tool as the mcp.ai marketplace, naming the full spectrum of actions (search, describe, invoke, install, list_tools, subscribe, cancel, report_bug, request_mcp, plus a prompt-library trio). It uses specific verbs+resources (discover MCPs, run tools one-off, install permanently) and the marketplace concept is distinctly different from sibling tools like authenticate, connect, or show_version. The scope is broad, but purpose is 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?

Excellent when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', explicit note that invoke works even when not installed, and clear handling of credential/wallet-failure flows (connect link, checkout link, then retry). It also defines search→describe→invoke as the core flow and flags installed_in_toolkit vs installed_in_workspace. The only gap is not naming sibling tools explicitly as alternatives, but internal guidance is thorough.

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=false, idempotentHint=true, and destructiveHint=false, so the description does not need to restate those. It adds minimal behavioral context—that the conversation is included for reproduction—but does not describe side effects (e.g., where the report goes, whether the user receives a ticket, rate limits). This is acceptable 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 consists of two sentences and every word contributes value. The first sentence states the purpose; the second explains what must be included for reproduction. No redundancy 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 relatively simple, side-effect-oriented reporting tool, the description gives the essential purpose, the primary message content, and the key reproduction detail (conversation). With no output schema, it could explain what happens after submission or how errors appear, but the existing coverage is adequate 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?

Schema description coverage is 0%, so the description must compensate. It clarifies the purpose of the 'conversation' parameter and implicitly addresses 'message' as the report content, but the 'context' parameter is entirely unexplained. Additionally, the schema defines conversation as a string while the description calls it an 'array', creating ambiguity about the expected JSON-encoded format.

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 a specific action—'Report a bug, missing feature, or send feedback'—and clearly identifies the resource. It distinguishes itself from unrelated sibling tools like authenticate, marketplace, or show_version, making the purpose unmistakable.

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 instruction to 'Include the conversation array with recent messages for reproduction' gives useful contextual guidance for using the tool, but there is no explicit statement about when to use this tool versus alternatives or when not to use it. Siblings are unrelated, so the context is implied rather than explicitly clarified.

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 communicate the safe, non-mutating behavior. The description adds the specifics of what versions are shown (platform and adapter), which is useful but minimal. 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?

The description is a single, clear sentence that directly states the tool's functionality. No wasted words, front-loaded with the action and subject.

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 zero parametershare no annotations, the description is sufficient to understand what the tool does. It doesn't promise more than it delivers hierarchical. There's no output schema, but the description implies it returns version info. For a simple tool, this 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?

There are 0 parameters, so the schema fully covers everything. With no parameters, the description doesn't need to add parameter-specific semantics, but it does mention the tool returns platform and adapter versions, which is an implicit output hint. Baseline for 0 params is 4.

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: it shows the current MCP platform and adapter versions. The verb 'Show' with specific resources distinguishes it from sibling tools like authenticate, connect, and marketplace.

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?

There is no guidance on when to use this tool versus alternatives or any context about use cases. It simply states what it does without placement among siblings 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds context on what data is returned (installed MCPs, connection status, accounts, catalog tool counts) and implies a snapshot of current state, which enriches the behavioral transparency beyond annotations. 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?

The description is a single succinct sentence that fronts the main action ('Returns the current toolkit state') and lists key data points. It's efficient and avoids fluff, though it could be slightly more structured with a colon or bullet-like listing for clarity, but it's still 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 no parameters, no output schema, and simple read-only semantics, the description is fairly complete. It specifies the four categories of information returned. However, it doesn't mention whether the output is formatted (e.g., JSON) or whether there are any connection-related caveats (e.g., some MCPs may not be responding). Given its simplicity, a '4' is reasonable, but a bit more detail on the nature of the state (e.g., real-time vs cached) would make it 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?

The tool has zero parameters, so the schema provides no parameter descriptions. The description compensates by clearly outlining the output scope (installed MCPs, status, accounts, tool counts), which gives semantic meaning to the tool's purpose. A baseline of 4 for zero-param tools is appropriate, and the description effectively explains what the user gets.

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, listing installed MCPs, connection status, accounts, and catalog tool counts. It uses a specific verb 'returns' and a specific resource 'toolkit state'. It is distinct from siblings like 'connect' and 'authenticate', 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 the tool is for retrieving a high-level overview of the toolkit's integration status, likely useful before or after connecting/authenticating. However, it doesn't explicitly state when to use it versus siblings like 'show_version' or 'marketplace', nor does it mention any prerequisites or exclusions.

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