MPF: Processos

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

Annotations already indicate idempotent and non-destructive behavior, so the bar is lower. The description adds important behavioral context by explaining the login flow, that no args returns a link, and how tokens are used for session login, without contradicting 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 bit longer but every sentence adds necessary information about the two authentication modes and the permanent config. It is well-structured, front-loading the main purpose and then explaining options.

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 no output schema and minimal parameter schema, the description covers the essential behaviors: how to log in, how to use the token, and the difference between permanent and session auth. It could mention response details or error cases, but it is sufficiently complete for invocation.

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 one optional 'token' parameter with no description (0% coverage). The description fully compensates by explaining that token is a JWT for session login, and that omitting it triggers a link response. This makes the parameter's meaning and usage crystal clear.

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 with MCP.AI by logging in via browser and obtaining an access token. It distinguishes between permanent config as a header and session-only token input, making the tool's function 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 guidance on when to call with no args (to get a link) versus with a token (session login), and describes the recommended permanent setup via config. It does not compare against sibling tools like 'connect', but the usage context is clear.

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 establish the tool as read-only, idempotent, and non-destructive. The description adds valuable conditional behavior: the difference between a fully connected state and a credentials-missing state, including the returned fields. This goes beyond what annotations alone provide.

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-loaded with the core purpose, and every clause adds meaningful detail. There is no fluff or repetition of annotation data.

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 return values and the two key states (all connected vs missing credentials). It is sufficiently complete for a zero-parameter status tool, though it could specify exact field names more precisely.

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 no parameters, and schema description coverage is 100% by default. The description does not need to explain parameters, and the baseline of 4 is appropriate since the tool's semantics are fully captured by its parameterless 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 tool's purpose: returning connection status and URLs. It provides specific behavioral details (authenticated:true, empty pending[], connect_url) that distinguish it from sibling tools like authenticate or show_version.

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 explains conditional outcomes but does not explicitly say when to choose this tool over alternatives. It implies usage as a status-checking tool, but there is no direct guidance on when not to use it or how it relates to the authenticate sibling.

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, the description discloses important behavioral traits: invoke works for non-installed MCPs via a one-off mechanism, credential needs surface as connect links, payment needs surface as checkout links, install makes tools permanently available, and write actions require workspace owner/admin. It also clarifies the prompt library is separate from MCP discovery. No contradiction with annotations exists.

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 dense but well-structured: opening definition, core flow with arrows, a KEY callout for the critical invoke behavior, then grouped mentions of install, list_tools, billing, writes, and the prompt library. Every sentence adds information, though the single-paragraph layout and the Portuguese word 'pontualmente' make it slightly harder to scan than an equivalent bulleted structure.

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 23 parameters, no output schema, and minimal annotations, the description covers a remarkable amount: the full workflow, permission model, billing/credential redirects, installed-state flags, and the prompt library. It is less complete on per-action return shapes/results and some parameter specifics, but for a gateway-style tool it provides enough context to select actions and invoke them 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?

With 0% schema description coverage across 23 parameters, the description carries heavy explanatory weight and does add real semantics to the action enum by walking through search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt-library actions. It also clarifies the role of mcp_id/tool_id in the flow and prompt variables/slug for prompts, though many smaller params (tier_slug, immediate, conversation, etc.) remain explained only by name or not at all.

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 immediately identifies the resource ('the official mcp.ai marketplace') and states its dual role as catalog and execution layer. It lays out a concrete core flow (search → describe → invoke) and adds specific capability examples, making the tool's purpose unmistakable and clearly distinct from generic helpers.

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 guidance: prefer invoke for one-off use, use install only for permanent toolkit additions, list_tools for currently callable tools, subscribe/cancel for billing, and request_mcp when nothing fits. It also explains when invoke will return connect/checkout links and that writes require owner/admin, which is strong alternative-selection 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 already state readOnly, idempotent, and non-destructive. The description adds valuable behavioral context beyond annotations: no platform credentials needed, payment per query via prepaid credit, data is public and non-confidential, and LGPD compliance responsibilities. This provides significant insight into how the tool operates.

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 front-loaded with the core purpose, then adds necessary contextual details about payment, data nature, and LGPD. It's slightly verbose with legal disclaimers, but every sentence contributes meaning, making it appropriately structured for the tool's complexity.

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 one ambiguous parameter, the description does not explain what the tool returns or how to format the query. It does clarify the data is public and from official sources, but missing return value and query format details leaves the tool incomplete for an agent to use 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 only parameter 'query' has zero description coverage in the schema, and the description does not elaborate on what format or content 'query' should take (e.g., process number, party name, court). Since the schema gives no hints and the description is ambiguous, this is a clear 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 states the tool's purpose: consulting MPF processes from an official source ('MPF: Processos, consulta em fonte oficial'). The verb 'consultar' (consult) and resource 'processos' are explicit, and it distinguishes itself from unrelated siblings like authenticate or 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?

The description provides context about when to use the tool: to consult official Brazilian public source information, noting it's not confidential and requires prepaid credit. However, it does not explicitly mention alternatives or exclusion cases, though the sibling tools are unrelated, making the usage fairly clear.

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 but no readOnly/destructive hints. The description does not contradict annotations. It adds context that sending the conversation array aids reproduction, which is useful. However, it doesn't disclose what happens after reporting (e.g., no response or confirmation) or any side effects beyond the idempotent hint.

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. Every sentence adds value, and it is appropriately sized for the tool's simplicity.

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 (3 params, no output schema), and the description covers the core usage. However, it lacks details on how the 'conversation' parameter should be formatted (e.g., JSON array as string) and what the 'context' parameter is for. Slightly incomplete due to missing parameter semantics.

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. The description mentions the conversation array for reproduction, which clarifies that parameter. However, it does not explain the meaning of 'message' or 'context' beyond their schema names. With low coverage, more parameter detail is needed.

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 identifies the resource (bug, feature, feedback). It distinguishes from siblings by focusing on user feedback rather than process queries or tool 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 specifies when to use it (when reporting bugs/feedback) and includes an instruction to include the conversation array. However, there is no guidance on when NOT to use it or alternatives (e.g., for other issues). Only partial usage context is provided.

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 the safety profile. The description adds the specific behavior of returning version information, which is helpful and does not contradict annotations, satisfying the 'beyond annotations' bar.

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?

One sentence of nine words, front-loaded with the verb and resource. Every word earns its place with no redundancy or padding.

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: no parameters, no output schema, and annotations cover side effects. The description fully specifies the returned information (MCP platform and adapter versions), making it complete for an agent to invoke 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?

With zero parameters, schema coverage is 100% and the baseline is 4 per the rubric. The description adds no parameter details, but none are needed.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('Show') and a clear resource ('MCP platform and adapter versions'), unambiguously distinguishing it from sibling tools like 'connect' or 'marketplace'. No other tool targets version discovery, so the purpose is precise and non-overlapping.

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 by simply stating the action, but it does not explicitly mention when to use this tool versus alternatives or note exclusions. For a trivial version-checking tool, this is acceptable but not exemplary; the context 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful detail about what state is returned, but does not disclose additional behavioral traits such as freshness, caching, or authentication requirements, leaving it at the baseline for annotation-backed tools.

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 front-loads the action and resource, then lists four concrete aspects of the returned state. Every clause adds useful information with no filler or redundancy.

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 informational tool with clear annotations and no output schema, the description sufficiently enumerates the full scope of returned information. It covers installed MCPs, connection status, connected accounts, and catalog tool counts, which is complete for this simple 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?

The tool has zero parameters, so the baseline of 4 applies. The description appropriately focuses on return contents rather than parameters, and there is no parameter-related ambiguity to resolve.

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 as 'current toolkit state'. It enumerates the exact contents returned (installed MCPs, connection status, connected accounts, catalog tool counts), making the tool's function unambiguous and distinct from siblings like show_version.

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 this tool is for inspecting toolkit state, but it offers no explicit guidance on when to use it versus alternatives such as connect, authenticate, or show_version. There are no stated exclusions or comparator sibling tools, so usage context is only implicit.

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