SINTEGRA: AL

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

Annotations indicate readOnlyHint=false (mutation) and idempotentHint=true. The description elaborates on the mutation by describing how it can set a permanent config header or a session-only token, and that calling with no args returns a login link. It does not explicitly state side effects like modifying server configuration, but the permanent token option implies that. 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 paragraph but packed with necessary details. It is front-loaded with the purpose and then branches into two usage modes. It is slightly dense and could benefit from bullet points, but every sentence earns its place 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 only one optional parameter, no output schema, and rich annotations, the description covers all needed aspects: how to authenticate (browser login, token retrieval, config header), invocation modes (with/without token), and session vs permanent behavior. It is complete and actionable 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 has 1 param (token) with 0% description coverage. The description compensates fully by explaining the token is optional, should be a JWT, and that it can be passed after the user pastes it, or omitted to receive a link. This adds crucial meaning beyond the bare 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: authenticate for IDE agents (Cursor, etc.) via browser login. It specifies the verb 'authenticate' and the resource (access token), and distinguishes it from siblings like connect and toolkit_info by focusing on the token-based authentication flow.

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?

Explicitly explains when to use which option: 'Best: add it to this server's config as a header... for a permanent, non-expiring connection' vs 'Or paste it here for a session-only login: call with { token: <jwt> }... or with no args to get the link.' This gives clear context and alternatives, effectively guiding the agent on invocation choices.

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 safety hints (readOnly, idempotent, non-destructive). The description adds valuable context beyond annotation by explaining conditional outputs (authenticated:true when all providers connected, connect_url when credentials missing). This gives agents a clear model of expected 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?

Two sentences, front-loaded with the primary purpose, and each sentence earns its place by describing a distinct behavior. No unnecessary 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?

There is no output schema, so the description must explain return values. It does so thoroughly: authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing. For a simple status tool, this 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?

With zero parameters, the schema is trivial (100% coverage). The description doesn't need to explain parameters; the baseline of 4 applies because all parameter-related information is already covered by the 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 uses a specific verb ('Returns') and names the exact output (connection status and URLs). It clearly distinguishes from sibling tools like 'authenticate' by focusing on status retrieval rather than performing 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 (e.g., when credentials are missing, it returns connect_url), but it does not explicitly state when to use this tool versus 'authenticate' or other siblings. No direct alternatives or exclusions are mentioned.

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?

Adds substantial behavioral detail beyond annotations: invoke works without installation, returns connect/checkout links on missing creds/funds, writes (install/uninstall/subscribe/cancel, hidden one-off install) require owner/admin. It also clarifies search/describe flag installation status. 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 lengthy but logically organized: it starts with the main purpose and flow, then details write operations, billing, and the prompt library. Some redundancy (multiple mentions of 'invoke') but each sentence adds value 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?

Covers the primary workflows (search/describe/invoke/install), auth requirements, billing, prompt library, and return behavior for key actions (connect link, checkout link). However, it omits details for less common actions like 'resume', 'cancel_reason' usage, and does not describe any output schema (since none exists). Overall, adequate for main 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?

The description explains the meaning of 'action' and some associated params (mcp_id, tool_id, arguments, etc.) but does not cover all 23 parameters. With 0% schema coverage, it should compensate more; for example, 'conversation', 'prompt_targets', and 'cancel_reason' are not explained. It adds some semantics but not enough for full usage.

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 is 'the official mcp.ai marketplace' and enumerates specific actions (search, describe, install, invoke, etc.) and the prompt library. It distinguishes itself from sibling tools by describing its unique catalog and execution capabilities.

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: it outlines the core flow ('action=search discovers MCPs → describe returns profile → invoke runs the tool'), and contrasts invoke vs install ('prefer invoke for a single/occasional use; use install only to make an MCP PERMANENT'), plus billing and auth prerequisites. It names alternatives like list_tools and subscribe/cancel.

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 idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds the context that the conversation array should be included for reproduction, but it does not disclose any side effects, such as whether the report is persisted or if authentication is required. Given the annotations, this is adequate but minimal—no contradiction.

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 primary purpose, and includes the only additional instruction needed. It is concise with no redundant or filler content, earning its place.

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 three parameters and no output schema. The description explains the purpose and the conversation parameter, but does not describe what should go into the 'message' (the required field) or what happens after submission (e.g., response format). For a simple reporting action, it is somewhat complete but leaves notable 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?

Schema description coverage is 0%, so the description must explain parameters. It only mentions the conversation parameter ('Include the conversation array with recent messages for reproduction'). The required 'message' parameter and the optional 'context' parameter remain unexplained. This partial coverage is insufficient for a tool with 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.' It uses a specific verb (report) and resource (bug/feature/feedback), and the sibling tools (authenticate, show_version, etc.) are all unrelated, so it effectively distinguishes itself. The added instruction about including the conversation array for reproduction further clarifies the tool's role.

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 the tool (for bugs or feedback) and provides explicit guidance on including the conversation array for reproduction. However, it does not mention when not to use it or name alternative tools, though the siblings are obviously distinct. There is a clear context but no 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, so the safety profile is fully covered. The description adds useful context by specifying that both MCP platform and adapter versions are returned, which is more specific than the tool name alone.

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 with no filler, repetition, or unnecessary detail. Every word contributes to understanding the tool's function.

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 version query, the description is complete and sufficient. The sibling context and annotations add no further requirements, so a longer description would add little value.

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 no parameters, so there is nothing for the description to clarify. Per the baseline for zero-parameter tools, the description is not expected to elaborate on parameter meaning.

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 the specific verb 'Show' with a clear resource ('current MCP platform and adapter versions'), making the tool's purpose immediately obvious. It distinguishes itself from sibling tools like report_bug or authenticate, and is not a tautology.

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 the tool is for checking version information but does not explicitly state when it should be preferred over sibling tools such as toolkit_info. Since the tool is trivial and has no parameters, the lack of explicit alternatives is understandable but still not 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?

Beyond annotations, description mentions prepaid credits, data non-confidentiality, and LGPD responsibility, adding behavior details but not exhaustive coverage.

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?

Description is a single paragraph with necessary details, concise and no redundancy, though it could be split for 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?

Description covers purpose and some operational aspects but lacks parameter explanations and output details, making it incomplete for effective use.

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 does not explain the parameters 'ie' and 'cnpj', leaving them ambiguous, and the schema has no descriptions.

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 it is a SINTEGRA AL query on official Brazilian sources, distinguishing it from authentication and other 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?

Description provides context about payment and credentials but does not explicitly state when to use this tool versus others, lacking guidance on use cases or alternatives.

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 this as read-only, idempotent, and non-destructive; the description adds value by specifying exactly what is returned rather than just saying 'info.' No behavioral contradictions or hidden side effects are indicated, and the description aligns well with 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 states the purpose and immediately enumerates the returned information. Every word contributes meaning, 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?

Given the tool has no parameters, complete annotations, and a low-complexity purpose, the description sufficiently covers all essential aspects. With no output schema, the enumerated return fields provide the necessary clarity for an agent to understand 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?

The tool has zero parameters, so the schema leaves nothing undocumented. The baseline for a parameterless tool is 4, and the description does not need to compensate for any parameter 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 ('Returns') and identifies a clear resource ('current toolkit state'), then enumerates the exact sub-components: installed MCPs, connection status, connected accounts, and catalog tool counts. This fully distinguishes it from sibling tools like show_version 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 clearly implies the tool is for inspecting the current state of the toolkit, but it does not explicitly state when to use it versus alternatives or mention any exclusion cases. Context suggests pre-connection or troubleshooting use, but that guidance is not stated.

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