SINTEGRA: SP

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

The description explains the mechanics (browser login, token handling) but does not explicitly state side effects such as whether a session is created or if state changes. The annotation indicates idempotent and non-destructive, and the description adds some detail about permanent vs session-only, but it could be more explicit about what happens after successful authentication.

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 verbose with 'Best:' and 'Or:' but remains logically structured and not overly long. It conveys all necessary information without redundancy, though it could be tightened.

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 primary use cases (getting a link, submitting a token) and clarifies the difference between permanent and session-based login. It does not mention potential errors or what happens after token submission, but for an authentication tool it is reasonably 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?

The only parameter 'token' is fully explained in the description: it is the JWT to authenticate with, and it is optional (call with token or no args). This gives complete meaning to the schema, which has no descriptions of its own.

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 to the server for IDE agents. It explains two usage modes (getting a login link or providing a token) and distinguishes itself from sibling tools like connect or show_version by focusing specifically on login/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 provides clear instructions on how to use the tool (call with token or no args to get link) and explains the difference between permanent and session-only authentication. It does not explicitly mention when to prefer this over alternatives, but the context makes it the obvious choice for login, so it is largely adequate.

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 tool is known to be safe. The description adds useful context about return states (authenticated:true and empty pending[], or connect_url), which is beyond annotations. It doesn't describe potential side effects or auth requirements, but for a read-only tool with strong annotations, this is acceptable.

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 ('Returns connection status and URLs'), and every sentence adds value: the second explains conditional behavior. No 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 the tool's simplicity (no parameters, no output schema, but annotations cover safety), the description is complete enough for an agent to understand when and why to call it. It clearly describes successful and pending states, which is adequate for a status-check 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 no parameters, and the schema coverage is 100% (trivially). The description adds meaning by explaining the output semantics (connection status and URLs) without needing parameter details. Since there are no parameters, the description is effective in conveying what the tool does, earning a 4.

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 returns connection status and URLs, and distinguishes it from siblings by focusing on read-only connection status, which is distinct from tools like authenticate or marketplace. However, it could be more specific in naming the exact resource (e.g., 'connection status' is clear but generic).

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 connection status and get URLs when credentials are missing. It does not explicitly name an alternative, but it contrasts with the 'authenticate' sibling, providing clear context for usage. However, it lacks explicit '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?

The description adds substantial behavioral context beyond the annotations: writes require workspace owner/admin, invoke performs a one-off hidden install, credential gaps return connect links, payment gaps return checkout/top-up links, and search/describe flag installed status. There is no contradiction 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?

The description is dense and front-loaded, with every clause adding useful information for a complex multi-action tool. It is a single block of text and could benefit from grouping or bullet structure, but it avoids waste and covers a large amount of ground efficiently.

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 14-action dispatcher with no output schema and no parameter descriptions, the description is unusually complete: it explains the core flow, install-vs-invoke tradeoffs, authentication/payment failure modes, permissions, and the prompt library. Minor omissions such as the resume action and the semantics of limit/query/immediate prevent a perfect score.

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 and 23 parameters, the description compensates by explaining the central action parameter and key linkages like tool_id, prompt_slug, prompt_vars, and the request_mcp flow. However, it does not systematically document all parameters such as limit, query, immediate, resume, tier_slug, conversation, and the cancel fields, though most are fairly self-explanatory.

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?

Clearly identifies the tool as mcp.ai's official marketplace catalog and execution layer, with a concrete scope: discover MCPs, describe them, invoke them, install them, and access the prompt library. It distinguishes itself from sibling tools by explaining the core search → describe → invoke flow and by naming adjacent capabilities like list_tools and request_mcp.

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 invoke vs install: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also names alternatives for specific situations, such as list_tools for currently callable tools, request_mcp for building a new MCP, and subscribe/cancel for billing.

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 idempotent, non-destructive, and non-read-only behavior. The description adds that conversation data should be included for reproduction, but it does not clarify what happens after submission (e.g., whether an issue is created, data leaves the environment, or whether there is any confirmation response). 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 short, front-loaded with the main purpose, and contains no filler. It earns its sentences, though the 'array' wording could be more precise and schema-aligned.

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 low-complexity tool with annotations and one required parameter, the description is minimally adequate. However, it omits the meaning of the optional context parameter, does not explain the expected format of conversation beyond 'array,' and provides no information about return values or post-submission behavior.

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 only addresses the conversation parameter, and it does so in a slightly misleading way: it says 'conversation array' while the schema defines conversation as a string. The required 'message' and optional 'context' parameters are not semantically explained.

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 (report/send) with a clear resource (bug/feedback), and it is easily distinguished from siblings like connect, marketplace, 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?

It provides clear when-to-use context by listing the intended scenarios: bug reporting, missing feature requests, and general feedback. It does not explicitly mention exclusions or alternative tools, but the sibling list makes the use case relatively obvious.

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 the specific scope of what versions are shown ('MCP platform and adapter'), but does not go beyond that to describe return format or side effects.

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, front-loaded with the action and object, and contains zero wasted words. It is optimally 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?

For a no-parameter, no-output-schema version query, the description fully conveys what the tool returns. It is sufficient for an agent to select and invoke the tool 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, the schema is trivially fully covered (100%). The description needs no parameter explanation; this baseline of 4 is appropriate since the tool takes no input.

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 resource ('current MCP platform and adapter versions'), clearly distinguishing this from sibling tools like authenticate or connect. It is concise and 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?

No guidance is provided about when to use this tool versus alternatives like toolkit_info, or when version info might be needed. The description implies usage by stating what it does, but lacks explicit context or 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 read-only, idempotent, non-destructive hints. The description adds valuable context: payment per query, no platform credentials needed, data is non-confidential, and LGPD compliance responsibilities. This goes beyond 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 relatively concise (four sentences) and front-loads the core purpose. Some redundancy exists ('consulta em fonte oficial' and 'Consulta informação de fontes e órgãos oficiais brasileiros' are similar), but it remains efficient overall.

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 no parameter explanations, the description fails to cover key operational details: what the parameters mean, whether either is required, and what the response contains. The legal/payment context is helpful but does not compensate for these 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 input schema lists 'ie' and 'cnpj' with no descriptions, and schema coverage is 0%. The description provides no explanation of what these parameters represent or how to use them, leaving the agent without essential information for correct invocation.

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 queries official Brazilian sources (SINTEGRA SP) with a specific verb ('consulta', 'Consulta informação'). It differentiates from siblings by specifying 'SP' and the official source nature, making its purpose 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?

No guidance is given on when to use this tool versus alternatives (e.g., other query tools, authenticate, marketplace). It mentions payment and hosting but does not specify scenarios or exclusions, leaving usage timing vague.

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, establishing this as safe read-only. The description adds value by revealing the exact contents of the returned state (installed MCPs, connection status, accounts, catalog tool counts), which is not otherwise visible. No output schema exists, so this disclosure is important.

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 sentence that front-loads the core purpose and then lists the specific data items. Every word earns its place with no redundant or vague phrasing.

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 info tool with no output schema, the description fully explains what will be returned: installed MCPs, their connection status, connected accounts, and catalog tool counts. This is sufficient for an agent to understand the tool's role within the toolkit.

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 takes zero parameters, so the schema trivially covers all inputs. Per the baseline for zero-parameter tools, a score of 4 is appropriate; there are no parameter semantics to elaborate.

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 begins with a clear verb 'Returns' and specifies the resource 'current toolkit state', then enumerates specific data: installed MCPs, connection status, connected accounts, and tool counts. This clearly distinguishes it from sibling operations 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 implies when to use it—whenever you need an overview of the toolkit—but does not explicitly state this or mention alternatives. Sibling tools like connect and authenticate exist but no contrast is provided. The usage context is evident from the description, so it rates a 3.

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