SINTEGRA: AC

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

Annotations already indicate readOnly false, idempotent true, destructive false. The description adds context about creating permanent vs. session-only connections and that calling with no args yields a link. It doesn't explicitly state side effects like state mutation, but it implies the auth flow. No contradiction—consistent 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 concise (three sentences) and front-loaded with core purpose. Every sentence adds value: process, best practice, alternative. Slightly verbose due to explaining both methods, but 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 auth flow complexity (two methods, token parameter, link retrieval) and no output schema, the description covers the essential steps and outcomes. It could specify the exact response when calling with token, but it's sufficiently complete for most use cases.

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 has only 'token' (string) with 0% description coverage. The description fully compensates by explaining that token is the JWT from browser and that it can be omitted to get the link. This adds crucial meaning beyond the raw 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: authenticating the user to the MCP server. It uses specific verb 'authenticate' and explains the process (browser login, token), distinguishing it from sibling tools like 'connect' or 'marketplace' by focusing exclusively on auth.

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 explicitly provides usage scenarios: best practice (header config for permanent connection) and alternative (session-only via pasted token). It also instructs when to call with token vs. no args to get the link. Clear guidance on when and how to invoke it.

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 and idempotent behavior. The description adds valuable conditional behavior: what occurs when all providers are connected vs. when credentials are missing, including specific return fields like authenticated and connect_url. This exceeds the annotations' minimal safety hints.

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 sentences, front-loaded with the core purpose, then concise conditional details. Every sentence is informative and no redundancy exists.

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, the description fully covers expected behavior across states. No output schema exists, but the description explains the key return values. Sibling tools are not needed for context.

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 input schema has zero parameters, so the baseline is 4. The description does not need to explain parameters. It adds context about the meaning of output fields, which is useful given the lack of an output 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 function: 'Returns connection status and URLs.' It uses a specific verb and resource, and distinguishes it from sibling tools like 'authenticate' by focusing on status rather than 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?

The description implies usage for checking provider connectivity, with clear context about what results to expect. It does not explicitly mention when not to use it or point to alternatives, but the read-only status-check purpose is evident.

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: it mentions that install/uninstall/subscribe/cancel require workspace owner/admin, that invoke runs one-off without installation, and that paid MCPs may return checkout links for billing. This provides substantial transparency about side effects and authorization, which is not present in 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 excessively long and repetitive. It redundantly explains the flow for both MCPs and prompts, and repeats the 'use install only...' guidance multiple times. While it is front-loaded with purpose, the verbosity and duplicated content detract from clarity and 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?

The description covers the overall workflow, including search, describe, invoke, install, and prompt operations, along with billing and permission notes. However, it does not elaborate on the JSON formats for 'arguments' or 'conversation', nor does it detail fields like 'cancel_reason' or 'prompt_vars'. Given the tool's complexity (23 parameters, 0% schema coverage), this leaves gaps that could confuse 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?

The description explains the main 'action' parameter and its enumerated values, and gives high-level context for parameters like 'immediate', 'tier_slug', and prompt-related fields. However, many parameters (e.g., 'arguments', 'conversation', 'cancel_reason') are not individually explained, and the schema has no descriptions, so the coverage of parameter semantics is partial.

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: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It also clarifies the core flow (search → describe → invoke) and distinguishes between MCP and prompt library functions, making it distinct from sibling tools like authenticate or 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?

The description provides explicit usage guidance, e.g., 'Use install only to make an MCP PERMANENT in the active toolkit; prefer invoke for a single/occasional use.' It also explains when to use describe vs. invoke and mentions that writes require owner/admin. This gives clear when-to-use direction, though it does not explicitly compare against sibling tools like authenticate or connect.

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 readOnlyHint=false (a write action) and destructiveHint=false. The description adds the instruction to include the conversation array for reproduction, which gives context on how the tool should be invoked. It doesn't contradict annotations, and the additional detail about reproduction is useful. However, it could expand on any side effects (e.g., external submission), but with annotations covering safety, the bar is lower.

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. The first states the purpose, the second provides an actionable instruction. No fluff or repetition, good front-loading.

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 a simple feedback mechanism. The description explains what to do (report and include conversation) but doesn't mention what happens after submission (e.g., any response or confirmation). Given no output schema, the agent might not know if a return value is expected. However, for such a tool, this is often implicit. It's complete enough for typical use, but slightly lacking on expected result.

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 explicitly mentions the 'conversation' parameter as a 'conversation array', but the schema defines it as a string with default '[]'. This could confuse the agent about the exact format. It does not explain 'context' or 'message' beyond the overall purpose. Since only one of three parameters is partially explained, it's adequate but not thorough.

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 specific (verb+resource) and clearly distinguishes it from sibling tools like authenticate, marketplace, or show_version, which have different functions.

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 actionable guidance: 'Include the conversation array with recent messages for reproduction.' This hints at when to use it (when you need to report an issue) and provides a key prerequisite. It doesn't explicitly mention when not to use it or alternatives, but the context is clear enough.

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 is consistent with the readOnlyHint and idempotentHint annotations, but it adds no extra context about side effects, authorization, or rate limits. Given the simple nature of the tool, the annotations already cover the main safety aspects.

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 with no unnecessary details, making it efficient and easy to parse.

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 parameters and no output schema specified, the description is complete enough for a simple informational tool. It fully conveys the tool's purpose without leaving gaps.

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, so the description has nothing to add beyond the empty schema. A baseline score of 4 is appropriate since there is no parameter information to clarify.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), making it distinguishable from sibling tools like authenticate or 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?

Although it does not explicitly mention when to use it versus alternatives, the purpose is self-evident for version queries. No competing tool is implied, and the description sufficiently guides 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which the description does not contradict. The description adds valuable context: the tool is hosted on the platform, requires no platform credentials, and users pay per query with pre-paid credit. It also clarifies data controller responsibility under LGPD, which is critical for legal compliance. These are genuine behavioral disclosures beyond 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 single paragraph, but it is information-dense and covers purpose, compliance, and operational details. It is not extremely long, but it is not front-loaded with the most essential usage information; the purpose is stated after the domain prefix. There is some redundancy ('consulta em fonte oficial' and 'informação de fontes e órgãos oficiais'), but overall it is reasonably 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's complexity: 4 parameters, no required parameters, no output schema, and no annotations for parameters, the description could be more complete. However, it covers the key operational and legal context (payment, hosting, LGPD compliance). It doesn't explain what the result looks like or which parameter combinations are valid, but since any of the four identifiers may be optional, providing usage examples would improve completeness. Still, for a read-only query tool with clear legal framing, it is fairly 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%, and there are 4 parameters (ie, cpf, cnpj, aceita_resultado_parcial). The description does not explain any parameter meanings or relationships Joshua, and the parameter names are cryptic (e.g., 'aceita_resultado_parcial' likely means 'accept partial result' but is not confirmed). Since coverage is 0%, the description should compensate but does not.

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 the tool performs a SINTEGRA AC (Acre state) query from official sources. It clearly names the resource (official Brazilian sources) and the verb 'consulta' (query). It distinguishes itself from siblings by specifying the state and official source nature, though it doesn't explicitly contrast with similar query tools if any exist.

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 when to use the tool: to obtain information from official Brazilian sources that is publicly available to citizens, not confidential data. It implies this is for legitimate LGPD-compliant purposes and notes that payment is required via pre-paid credits, clarifying the operational context. It does not explicitly mention alternatives, but given the obscure sibling list, the context is clear enough.

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 cover read-only and non-destructive behavior. The description adds detail about the content returned but does not disclose potential side effects, rate limits, or failure modes. With annotations present, the description barely extends beyond 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, front-loaded sentence that immediately communicates the action ('Returns') and the key output elements. No fluff or repetition.

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 status tool with no parameters and no output schema, the description covers the return content sufficiently. It lists the main data points without over-explaining. Could mention if it returns errors or includes empty lists, but overall 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?

The tool has zero parametersessed, so the schema is fully described (100% coverage). The description adds no parameter info, but none is needed. Baseline is 4 for no 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 that the tool returns the current toolkit statearenas and enumerates specific output elements (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource description that 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?

The description implies usage for obtaining an overview of the tool state, but provides no explicit guidance on when to prefer it over alternatives or when not to use it. Context is inferable but not stated.

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