Sivisa: SP

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

The description discloses behavioral traits beyond annotations: it explains that calling with no args returns a link, and that passing a token enables session-only login, while config-based tokens give non-expiring access. Since annotations only provide idempotentHint and non-destructive flags, this context adds value about mode-dependent behavior.

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 long but every sentence contributes useful information. It is front-loaded with the main purpose, then gives two usage scenarios in a structured way. It avoids redundancy and is well-organized, though it could be slightly trimmed without losing clarity.

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 output schema and involves authentication, the description adequately covers the workflow: getting the token, using it in two modes, and even suggests a config alternative. It doesn't describe return values, but for an auth tool that's acceptable. The guidance is complete enough for an agent to decide when and how to invoke it.

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?

Despite the schema having no description for 'token' and 0% coverage, the description explicitly defines it: 'call with { token: "<jwt>" } after the user pastes' and clarifies that it's a JWT. It also explains that the parameter is optional (call with no args to get the link). This fully compensates for the schema's lack of semantics.

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 purpose: 'log in in the browser, copy the access token' and how to use it for authentication. It distinguishes itself from sibling tools like 'connect' and 'marketplace' by focusing on authentication, though it doesn't explicitly name alternatives. The verb 'authenticate' plus the explanation makes the purpose clear.

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 guidance: it says to call with a token for session-only login or with no args to get the link, and recommends adding the token as a header for permanent access. It doesn't mention when not to use the tool or compare directly to siblings, but the context for when to use it 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 declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds valuable context beyond this by explaining the conditional response format (authenticated:true vs. connect_url), which is not evident from annotations alone. This enhances the agent's understanding of what the tool returns.

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 sentences, front-loaded with the main purpose, followed by conditional specifics. Every sentence adds value with no redundancy or filler, making it efficiently structured for agent comprehension.

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 (no parameters, no output schema), the description adequately covers both primary states (all connected vs. missing credentials) and the nature of returned URLs. It provides sufficient context for an agent to understand expected behavior without additional documentation.

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 there is nothing to describe. Per the rule for 0-param tools, a baseline of 4 is appropriate since the schema is trivially complete and the description needs no additional parameter explanation.

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: 'Returns connection status and URLs.' It specifies distinct behaviors for connected vs. missing credentials, and the resource (connection status) is well-defined. It also implicitly distinguishes itself from sibling 'authenticate' by focusing on status rather than initiating authentication.

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 connection status, but it does not explicitly state when to use this tool over alternatives like 'authenticate' or other siblings. There is no mention of when not to use it or any exclusions, leaving the agent to infer context from the tool's purpose alone.

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 key behavioral aspects beyond the annotations: invoke works even if MCP not installed, returns connect/checkout links, and writes require owner/admin. It also clarifies that install makes MCPs permanent in the toolkit, and describes the prompt library's behavior. This is far beyond the minimal annotation hints (openWorldHint=true, readOnlyHint=false).

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 with run-on sentences and many semicolons, making it hard to scan. While informative, it could be structured with bullet points or separated into logical sections (core flow, actions, permissions, prompt library). The lack of formatting hurts usability for an AI agent trying to quickly extract key 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 tool's complexity (23 parameters, 14 actions) and no output schema, the description does a decent job covering core flows (search→describe→invoke) and important behaviors (connect links, checkout, permissions). However, it omits details on return formats, error handling, and some parameters/actions (e.g., resume, report_bug specifics). It is complete enough for basic usage but not exhaustive.

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 explains core parameters like action, query, mcp_id, tool_id, and prompt-related fields. However, many parameters (e.g., arguments, conversation, tier_slug, cancel_reason) are not mentioned or exemplified, leaving gaps for an agent to infer their usage. The description covers the most important aspects but is not exhaustive.

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 official mcp.ai marketplace, covering discovery, execution, and management of MCPs and tools. It distinguishes itself from siblings by explaining its meta-functionality (search/describe/invoke/install) and its unique role as the catalog and runtime for the entire platform.

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 extensive guidance on when to use each action (search, describe, invoke, install, list_tools, subscribe, cancel, report_bug, request_mcp) and explicitly contrasts invoke vs install (prefer invoke for single/occasional use, install for permanent). It also states permission requirements for writes and how to handle connect/checkout links.

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 declare idempotentHint: true and readOnlyHint: false, so the description doesn't need to restate safety. It adds useful guidance about including the conversation array for reproduction, which helps the agent provide complete information. However, it doesn't disclose any side effects (e.g., where the report goes) or response behavior, so beyond the annotation-provided context, the added value is limited.

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: the first states the core purpose, the second provides a specific usage hint. It is front-loaded and every sentence carries meaningful information with zero wasted words.

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 a 3-parameter schema with no output schema and minimal annotations, the description is too sparse. It fails to explain the content format for the required 'message', the purpose of 'context', or any expected response. It also doesn't mention whether this tool sends data externally or if there are limitations. For a tool with multiple parameters, this is inadequate.

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 explain all parameters, but it only mentions the conversation array. The required 'message' parameter is not described (what should it contain?), and 'context' is completely ignored. The description fails to compensate for the schema's lack of field documentation, leaving the agent guessing about the meaning of two of three parameters.

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.' This is a specific verb+resource combination that directly indicates the tool's function. It distinguishes itself from siblings like authenticate, connect, and marketplace, which cover different domains.

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 provides usage context by defining the three scenarios (bug, missing feature, feedback). It does not explicitly state when not to use it or name alternatives, but given the sibling list, no other tool is suitable for reporting issues, so the guidance is clear enough. A minor deduction for lack of explicit 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, covering the safety profile. The description adds value by specifying that both platform and adapter versions are returned, but does not describe any additional behavioral details like output format or potential empty responses.

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 is clear and free of unnecessary detail. Every word contributes to explaining the tool's purpose, making it highly effective.

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 read-only version lookup with no parameters and no output schema, the description fully covers the necessary context. Annotations provide the safety profile, and the description covers the exact scope of the version information returned. No additional explanation is needed.

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 100% schema coverage trivially, so there are no parameter semantics to explain. The description appropriately focuses on what the tool returns rather than inputs.

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 clear resource ('current MCP platform and adapter versions'), which unambiguously states what the tool does. This distinguishes it from the sibling tools like authenticate or toolkit_info by focusing specifically on version 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 usage is implied: when you need to know the current MCP or adapter version, this is the tool to call. However, the description does not explicitly state when to use this over alternatives, nor does it provide 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.

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

Annotations already indicate readOnly, idempotent, and non-destructive. The description adds that it requires prepaid credit, does not use platform credentials, and handles non-confidential data with LGPD compliance. This adds some context but does not clarify return values or side effects beyond what annotations imply.

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 concise but includes legal and billing details that are not directly actionable for an agent. It front-loads the main purpose but then digresses into contractual info, making it less focused than ideal.

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 sparse parameter info, the description should explain what the tool returns and how to pass inputs. It does neither. The legal/commercial context is present but does not compensate for the lack of technical guidance, leaving the tool underspecified for an agent.

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% and the description does not explain the meaning or format of 'cpf', 'cnpj', or 'municipio'. Since the schema only lists types, the description fails to clarify which parameter is needed for what query, leaving the agent without essential input semantics.

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 it queries information from official Brazilian sources ('consulta em fonte oficial', 'Consulta informação de fontes e órgãos oficiais brasileiros'), which is a specific verb+resource. It distinguishes from siblings like authenticate and show_version, but does not specify what exact information (e.g., CPF/CNPJ lookups) it provides, leaving some ambiguity.

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 given on when to use this tool versus alternatives, nor any prerequisites or exclusions. The description focuses on legal/payment aspects rather than usage context, so an agent has no criteria for selecting it over other 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, idempotentHint=true, destructiveHint=false. The description adds no contradictions and provides complementary context about what is returned (installed MCPs, connection status, accounts, catalog tool counts). It appropriately relies on annotations for safety, adding value about output scope.

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 efficiently lists the key elements of the toolkit state. Every phrase adds value: installed MCPs, connection status, accounts, and catalog tool counts. 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 parameterless read-only info tool with robust annotations, the description fully covers what the agent needs to know: what state is returned and its scope. No output schema is present, but the description clearly enumerates the return content, making the tool well-specified.

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% (empty schema). The description fully explains what the tool returns, compensating for the absence of parameters. This is a baseline 4 for parameterless tools that clearly describe their functionality.

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 is specific and distinguishes itself from sibling tools like authenticate or connect, which handle actions rather than state 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 when to use this tool (to check toolkit state and connections) but provides no explicit guidance on when not to use it or alternatives. Given siblings like show_version focus on version info, the context is clear enough for basic use, but exclusions are not stated.

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