Conselho Federal de Psicologia: Cadastro

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

Describes the behavior beyond annotations: no-arg call returns a login link, token call performs a session login, and configuration allows a permanent connection. This adds context to the annotations (idempotentHint=true, readOnlyHint=false) without 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 only two sentences but is somewhat rambling, mixing configuration advice with direct usage instructions. It is informative but could be better organized 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?

Covers the three usage scenarios (no args, with token, permanent config) and mentions the returned login link. Despite lacking an output schema, it provides enough detail for an agent to call the tool effectively.

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 an optional string with no description (0% coverage). The description clarifies the token is a JWT and explains both calling conventions (with token and with no arguments), effectively compensating for the schema gap.

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 explains the tool is for authenticating to MCP.AI by obtaining an access token via browser login or accepting a pasted JWT. It uses specific verbs and resources and conveys the core purpose, though it does not differentiate from sibling tools like '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?

Provides explicit guidance on when to use the permanent token configuration (via server config header) versus session-only login (passing the token), and mentions the no-args call to retrieve the login link. It gives clear context and usage modes, though it doesn't compare against 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 declare readOnlyHint=true and destructiveHint=false. The description adds useful context: it's a paid service (pre-paid credits), data is not confidential, and the client is data controller under LGPD. This exceeds the minimal burden given 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 and front-loaded with the key purpose. It includes important usage and legal notes but remains compact. Not excessively verbose, but could be slightly more 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?

The tool has 5 optional parameters and no output schema. The description gives enough context for an agent to understand it's a read-only, paid query to official source. It doesn't explain return value structure, but with no output schema, that is expected. It lacks info on parameter combinations (e.g., minimum requirements), but overall it's 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%, so the description must compensate. It doesn't explain the parameters (uf, cpf, cnpj, nome, registro) but they are self-explanatory given the domain. The description does not add parameter-specific details like formats or required combinations. Baseline is 3 due to zero coverage, but it doesn't go beyond that.

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 query the Federal Council of Psychology registry from the official source. It specifies the resource (official Brazilian bodies) and differentiates from siblings (which are platform-level 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?

It explains this is a paid consulta with pre-paid credits and that it queries official sources. It doesn't explicitly name alternatives, but siblings are clearly not related. It gives context on when to use this (for official data consultation) and implies when not to (not for confidential data).

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 destructiveHint, so the description's added detail about returning different states (authenticated:true vs connect_url) provides meaningful behavioral context beyond structured fields, 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?

Two concise sentences, front-loaded purpose, and no redundancy. Every clause adds value.

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, read-only status tool with no output schema, the description fully explains the return variations (authenticated vs missing credentials) and is 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?

Tool has 0 parameters, so baseline is 4. Description adds no param-specific info, but none is needed; the conditional logic fully covers behavior.

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?

Description clearly states 'Returns connection status and URLs' with specific verb and resource, and distinguishes from siblings like authenticate and marketplace by focusing on status.

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 conditional behavior (when connected vs credentials missing) but does not explicitly state when to prefer this tool over alternatives like authenticate. No direct exclusions or alternative recommendations.

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 discloses several behavioral nuances beyond the annotations: invoke runs one-off without bloat, returns connect/checkout links for missing credentials/funds, and requires workspace owner/admin for writes. It also explains that search/describe flag installation state. No contradiction with annotations; it enriches them substantially.

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 structured logically: core flow first, then invoke specifics, installation vs temporary, and finally prompt library. Every sentence contributes to distinguishing usage. It sacrifices brevity for completeness, which is justified given the tool's complexity, but could be slightly tightened to avoid overwhelming the agent.

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 23 parameters, no output schema, and 14 distinct actions, the description covers all major aspects: the full action list, the distinction between one-off vs permanent, auth requirements, link generation, prompt library, and even error handling (retry after checkout). It leaves little ambiguity about what to 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?

With 0% schema description coverage, the description must compensate for all 23 parameters. It does so by explaining the meaning of the action enum and key parameters like mcp_id, tool_id, arguments, and the prompt library's prompt_title, prompt_vars, etc. While it doesn't enumerate every field, it gives enough context to infer most parameter purposes through the described workflows.

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 is exceptionally clear: it identifies the tool as 'the official mcp.ai marketplace' and explains its dual role as catalog and execution engine. It lists multiple concrete use cases ('find an MCP that does X', 'consulta um CPF') and describes the core action flow (search→describe→invoke), clearly distinguishing it from sibling tools by position as the central hub.

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 for each action: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and explains the distinction between list_tools (what is callable now) and search/describe. It also names alternatives like report_bug and request_mcp, giving a complete decision tree for when each sibling action is appropriate.

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 provide readOnly/destructive/idempotent hints, so the bar is lower. The description adds that conversation data is used for reproduction, but it does not disclose what happens after reporting (e.g., confirmation, ticket/ID, or side effects of repeated submissions).

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 short and front-loaded, using two sentences effectively. The only flaw is the imprecise 'conversation array' wording, which introduces ambiguity.

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 tool is simple with three parameters and no output schema, and the description conveys the overall purpose well. However, it is not fully self-sufficient because it does not clarify the required message field and misstates the conversation field type.

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 carries the full burden for parameter meaning. It mentions the conversation parameter but calls it an 'array' while the schema types it as a string; it also ignores the required 'message' parameter and the optional 'context' parameter.

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 clearly lists targets: bug, missing feature, or feedback. It is distinct from sibling tools like authenticate, show_version, 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?

The description identifies concrete use cases (bug, missing feature, feedback) and instructs the agent to include conversation data for reproduction. It does not explicitly state when not to use the tool, but no close alternatives exist among the siblings.

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, covering safety profile. The description adds 'current' implying no historical data, and is consistent with annotations. It provides minimal extra context beyond structured fields, so 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 a single, concise sentence that conveys the essential purpose without waste. Perfectly front-loaded 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 the tool's simplicity (no parameters, no output schema, clear annotations), the description fully covers what the agent needs to know. It is complete for its trivial scope.

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)Skip schema coverage is trivially 100%. With no parameters to explain, the description need not add detail. Baseline for 0 params is 4; the description does not need to compensate, so a 4 is justified.

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: showing current MCP platform and adapter versions. It specifies the exact resource (versions) and distinguishes itself from generic sibling tools like toolkit_info, which likely provides broader system information.

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 does not explicitly state when to use or not use this tool, nor does it mention alternatives. It implies usage for checking versions, but gives no guidance on scenarios or exclusions. It meets the baseline for readability but lacks proactive direction.

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, destructiveHint=false, and idempotentHint=true. The description adds value by detailing the exact content of the returned state (installed MCPs, connection status, etc.), 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 a single, focused sentence that immediately states the tool's purpose and the specific data it returns. 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?

Given the zero-parameter schema and informative annotations, the description fully describes the tool's output scope. It does not need to explain return formats or caveats since this is a simple state query with clear content.

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 Secretly, so the description carries no parameter burden. Schema description coverage is 100% (no params to document). A baseline of 4 is appropriate since parameters are not applicable.

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 states the function: 'Returns the current toolkit state' and enumerates specific elements (installed MCPs, connection status, connected accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate or connect, which perform actions rather than inspection.

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 toolkit state, which is distinct from the action-oriented siblings. However, it doesn't explicitly state when not to use it or mention alternatives, though the sibling list makes the context clear.

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