Conselho Regional de Odontologia SP: Cadastro

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

Annotations already indicate non-read-only and idempotent behavior. The description adds useful context: it explains the permanent vs. session-only effects and how the token is used. It does not contradict annotations and adds behavioral detail beyond the schema.

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 sized, with each sentence contributing to understanding the auth flow. It is well-structured with 'Best:' and 'Or' to separate options, though slightly verbose. It could be tightened but remains efficient and front-loaded.

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 single-purpose authentication tool with no output schema, the description covers the key aspects: login flow, gating (permanent vs. session), and call patterns. It lacks error handling details, but that's not critical given the simplicity. The description is sufficiently complete for an agent to use the tool 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?

The schema only defines 'token' as a string, but the description explains its meaning and usage: the token is a JWT pasted by the user, and calling with no args returns a link. This adds significant semantic value, compensating for the 0% schema description coverage.

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: authenticating to MCP.AI for IDE agents. It specifies the action (log in, copy token) and distinguishes from siblings like 'connect' by focusing on the authentication flow, making it 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?

The description provides explicit when-to-use guidance: either add token to config for a permanent connection or paste it for session-only. It explains the two call variants (with token or no args) and when each is appropriate. However, it does not explicitly mention when not to use this tool or alternatives, so a minor gap remains.

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 well covered. The description adds useful context about the two return scenarios (all connected vs missing credentials). However, it does not disclose potential rate limits, latency, or what 'per-install URLs' means in detail.

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 sentences, front-loads the purpose, and uses clear conditionals to explain the output. Every sentence adds value, and there is 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?

Given the tool's simplicity (zero parameters), the description covers the main behavior and output scenarios sufficiently. It lacks an explicit statement that no arguments are needed, but that is trivial to infer from the schema. The complexity is low, so completeness is high.

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 schema coverage is 100% (vacuously). The description explains the return behavior in terms of states, which is the key semantic information. This is fully adequate since there are no parameters to document.

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, and it explains the two possible states (all connected vs missing credentials). This is clear and distinct from siblings like 'authenticate' and 'marketplace', though it could be more explicit about being a status/read-only 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 implicitly suggests using this tool to check connection status before proceeding with authenticated actions, but it does not explicitly mention when to use it over siblings or when not to use it. The context is clear enough for an agent to infer, but explicit guidance is missing.

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 non-destructive behavior. The description adds valuable context beyond these: it requires no platform credentials, is paid per query with prepaid credit, data is from official Brazilian sources and not confidential, and the client is the data controller under LGPD. This enriches the behavioral profile without contradicting 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 concise, with the key purpose stated in the first clause ('Conselho Regional de Odontologia SP: Cadastro, consulta em fonte oficial') and additional context in subsequent sentences. It avoids verbosity and unnecessary details, though the legal and payment info could be considered slightly tangential, it still fits in a compact paragraph.

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 a single parameter and no output schema, the description covers payment, credential, and data sensitivity context, which is useful. However, it does not describe what the response contains (e.g., status, name, validity), nor does it mention any caveats like rate limits or caching. Given the lack of output schema, the agent has no information about expected return structure, so completeness is partial.

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 sole parameter 'inscricao' is not explained in the description at all; schema description coverage is 0%. The parameter name is self-explanatory (likely meaning registration number), but the description does not confirm its format, required pattern, or what value to pass. Since the description does not compensate for the missing schema documentation, the agent must rely on the parameter name alone, which is insufficient.

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 'Cadastro, consulta em fonte oficial' (Registration, query from official source), clearly indicating it's a query operation for registration data from an official dental council. The name 'cro_sp_cadastro_consultar' further specifies the CRO SP context, distinguishing it from unrelated siblings like 'authenticate' and 'marketplace'. However, it does not explicitly mention that the query is about dentists or what exact 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 provides no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. It does state that the query is paid via prepaid credit and requires no platform credentials, which could imply strategic usage, but it does not explicitly advise when to invoke this tool or when to prefer another. No comparison to sibling tools is given.

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?

Despite having annotations (readOnlyHint=false, openWorldHint=true), the description adds substantial behavioral context: invoke runs one-off without installing and without bloating the tool list, returns connect/checkout links for auth/wallet failures with retry instructions, flags installed_in_toolkit vs installed_in_workspace, and discloses that writes require workspace 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 a single information-dense wall of text with no sections, bullets, or paragraph breaks separating the marketplace flow from the prompt library. Every sentence carries value given the tool's complexity, and the core flow is front-loaded, but the structure does not help an agent parse it rapidly.

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 14-action multiplexer with no output schema and zero schema parameter descriptions, the coverage is strong: it explains the core flow, one-off invoke semantics, auth/billing link behavior, install-vs-invoke distinction, list_tools, the prompt library trio, and permission requirements. Minor gaps remain on resume, uninstall details, tier_slug, and immediate, but the main behaviors are 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?

Schema description coverage is 0%, so the description must compensate, and it does explain the action-driven flow conceptually (action enum values, mcp_id, tool_id, arguments). However, with 23 parameters it leaves many unexplained (immediate, tier_slug, limit, message, request_*, prompt_*, cancel_reason/cancel_comment), and the prompt library params are only lightly referenced. Partial compensation at best.

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 specific purpose: the mcp.ai marketplace catalog plus the execution mechanism for every MCP/tool, covering capability requests. It gives concrete examples ('find an MCP that does X', 'consulta um CPF') and clearly enumerates the core flow (search → describe → invoke), distinguishing itself from siblings like authenticate and connect by defining its own domain.

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?

Extensive when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT in the active toolkit', and it maps each action to its trigger (subscribe/cancel for billing, report_bug for feedback, request_mcp for new builds). It also explains the search → describe → invoke flow sequence, giving the agent a decision path.

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=false (side effects possible) and idempotentHint=true, but the description does not elaborate on these behaviors. It does mention the need for conversation data, adding some transparency about input requirements, but lacks details on outcomes or error handling.

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, consisting of two short sentences. It conveys the essential purpose and one key usage detail without unnecessary elaboration 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?

Given no output schema and simple parameters, the description is fairly complete. It covers the core intent and the important reproduction context, but could briefly mention the other parameters or expected outcome for fuller completeness.

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 includes three parameters (message, context, conversation) but the description only explicitly explains the purpose of the conversation parameter. It does not clarify the role of 'message' or 'context', leaving partial coverage of parameter meanings.

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 distinguishes this from sibling tools like authenticate or show_version by focusing on feedback and issue 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?

It gives implicit guidance by instructing to include the conversation array for reproduction, but does not explicitly compare with alternative tools or state when not to use it. The context of bug reporting is clear enough for typical 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well established. The description adds minimal behavioral context beyond stating it shows current versions, but this is sufficient for a read-only query tool with no side effects.

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 fully articulates the tool's function without wasted words 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?

This is a trivial, parameterless, read-only tool with safety-related annotations. The description is sufficiently complete for an agent to select and invoke it correctly; no return format or additional context is necessary.

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 input schema is empty; with no parameters to document, the baseline of 4 is appropriate. 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 uses a specific verb ('Show') and specifies the exact resource ('current MCP platform and adapter versions'), making the tool's purpose clear and distinguishing it from sibling tools like authenticate or 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?

The description implies appropriate use when checking platform or adapter versions, but it provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. For such a simple, obvious tool, the implied usage 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 declare readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds useful behavioral context by detailing exactly what state information is returned, which goes beyond the annotation metadata. No side effects are described, but none are expected given 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?

A single, front-loaded sentence with no filler. Every word adds value by specifying the return content, making it both concise and structurally sound.

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, and rich annotation metadata, the description sufficiently covers what the tool returns. Since there is no output schema, the description's enumeration of return fields is adequate for an agent to understand the tool's purpose and output expectations.

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, which warrants the baseline of 4. Schema coverage is complete for the empty property set, and the description does not need to explain parameters that do not exist.

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 ('current toolkit state') while enumerating exactly what information is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like show_version 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 about when to use this tool versus alternatives such as show_version or connect. The intended use is only implicit from the nature of the tool; there are no explicit context cues, 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.