SINTEGRA: AP

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

Beyond the annotations (idempotent, non-destructive, non-read-only), the description adds meaningful behavior: the permanent non-expiring connection, session-only scope of pasted tokens, and the conditional behavior of no-args returns the link. No contradictions.

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 efficiently structured with an introductory context sentence followed by practical instructions. The 'Best:' versus 'Or paste it here' framing makes the two main options easy to parse. It is slightly denser than strictly necessary but every sentence earns 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?

For a one-parameter, optional-token auth command, the description adequately covers the intents, the login flow, the permanent vs session distinction, and the no-args behavior. It does not specify the response format besides getting the link, but with no output schema, this is a minor gap.

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 only defines 'token' as a string with no description (0% coverage). The description compensates by explaining the exact usage: 'call with { token: "<jwt>" }' or call with no arguments, adding crucial meaning that the schema cannot provide.

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 the server to MCP.AI for IDE agents, with login in a browser and token-based connection. It uses a specific verb and resource, and while it doesn't explicitly contrast with sibling 'connect', its auth-only scope is unmistakable.

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 strong practical guidance: it recommends permanent config-based auth, explains session-only token paste for one-off login, and tells the agent to call with no args to obtain the login link. It lacks explicit 'when not to use' or references to sibling tools, but covers the main usage paths well.

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 readOnly, idempotent, and non-destructive behavior. The description adds valuable context about response variations: authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing. 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?

Two sentences, front-loaded with the core purpose, and every clause adds meaningful detail about 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?

For a zero-parameter status tool with no output schema, the description fully explains the return behavior in both connection states. It covers the main scenarios an agent would encounter and needs no additional 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?

Tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and the schema is trivially complete with 100% coverage.

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 the tool returns connection status and URLs, with a specific verb ('Returns') and resource ('connection status'). It distinguishes itself from sibling tools like authenticate by focusing on status 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?

Usage context is implied: this is the tool to check connection status and obtain URLs. It describes conditional behavior based on provider connection state, but does not explicitly contrast with alternatives such as authenticate or toolkit_info.

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, it discloses that invoke performs a one-off install even if the MCP is not installed, that install adds tools natively to future sessions, and that auth/payment failures return connect/checkout links to send the user. These side effects and prerequisites are exactly the kind of behavioral detail annotations cannot capture.

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 long but well-structured: the core flow is front-loaded with arrows, KEY is bolded, and related actions are grouped logically. Every sentence adds useful distinctions, though the dense list of all 14 actions in the latter half makes it heavy to parse at a glance.

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 14 actions, 23 parameters, and no output schema, the description covers the main journeys—search/describe/invoke, install vs invoke, credential/payment handling, and prompt publishing—very well. It omits the semantics of the 'resume' action, the return shape of search/list_tools, and the prompt-specific parameters, which are 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?

With 0% schema description coverage and 23 parameters, the description compensates for the central action parameter by explaining the meaning of search, describe, invoke, install, list_tools, subscribe/cancel, and the prompt actions in context. However, many parameters such as prompt_*, cancel_*, immediate, and tier_slug are not given semantic hints, so the agent must infer their meaning from names/enums.

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 marketplace as 'the in-platform catalog of every MCP/tool, AND the way to run them', and lays out the core search → describe → invoke flow. It also distinguishes prompt-library actions from MCP actions, so the tool's purpose is unambiguous even with 14 possible actions.

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 says when to use invoke vs install: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also explains the credential/payment retry flow and the requirement for workspace owner/admin on writes, giving clear when-to and when-not-to 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=false and idempotent=true. The description does not add context about what happens after reporting (e.g., ticket creation, data transmission) or clarify the idempotent behavior. It does instruct on submitting conversation data, which adds some transparency, but falls short of describing the full behavioral implications.

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 with no redundancy. It front-loads the purpose and then adds a single actionable instruction, making it concise and well-structured.

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 core usage but omits details about what happens after submission and leaves parameter semantics under-explained. Since there is no output schema, the return behavior is also unspecified. While adequate for a simple tool, it could be more complete given the zero-coverage schema.

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 zero description coverage, so the description must compensate. It only mentions the conversation array, providing a hint about its purpose, but does not explain the 'message' or 'context' parameters. The format of the conversation array (string containing a JSON array) is also not clarified, leaving ambiguity.

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 with a specific verb 'Report' and three supported intents (bug, missing feature, feedback). It is distinct from sibling tools, none of which are related to issue reporting. The instruction to include the conversation array further clarifies the scope.

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 context for when to use the tool (any bug, missing feature, or feedback) and explicitly instructs to include the conversation array for reproduction. It does not mention alternatives or exclusions, but since sibling tools are unrelated, the guidance is sufficient without needing 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 safety behavior is covered. The description adds no extra behavioral details beyond the purpose (e.g., no mention of output format, speed, or network dependency). With annotations present, the description meets the minimum bar but doesn't enrich understanding.

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, compact sentence that conveys the complete purpose without any fluff. It is front-loaded and uses every word effectively.

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 parameters and a simple purpose, the description is largely complete. However, because there is no output schema, mentioning the return format (e.g., text or JSON) would add clarity. Still, the core intent is clear, and the simplicity lessens the need.

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 per the rubric, a baseline of 4 applies. The description correctly omits parameter details since none exist, and it adds nothing that contradicts the schema. No further compensation 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 function: 'Show the current MCP platform and adapter versions.' It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), and it's distinct from siblings like toolkit_info which likely covers broader information. Clear 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 on when to use this tool versus alternatives. While it's straightforward to infer (e.g., when version info is needed), there is no explicit mention of context, prerequisites, or exclusions. The description only states purpose without usage context.

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. The description adds meaningful context: it is hosted on the platform without credentials, pay-per-query with prepaid credit, the data is not confidential, and the client is the controller under LGPD. This exceeds the annotation baseline and provides useful operational and legal transparency.

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 that front-loads the core purpose ('SINTEGRA: AP, consulta em fonte oficial') and then adds necessary commercial and legal context. It is not overly verbose and earns its length with relevant details.

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 query tool with no output schema, the description should mention parameter requirements (e.g., at least one of IE/CNPJ) and possibly the response format. It does not. The description adequately conveys the tool's nature but leaves gaps in usage specifics.

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' at all. Schema coverage is 0%, and the description fails to clarify how they are used (e.g., one or both required, input format). The parameter names are suggestive but not explanatory, and the description offers no compensation for the low schema coverage.

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 it is a consultation tool for SINTEGRA AP, an official Brazilian source, with a specific verb 'consulta' and resource. It distinguishes itself from sibling tools (which are about authentication, reporting, etc.) by emphasizing its domain-specific function.

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 context (official source, paid, LGPD) but does not explicitly state when to use this tool over alternatives or exclude any situations. Sibling tools are unrelated, so no direct conflict, but the guidance is implicit rather than explicit.

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 disclose readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds useful behavioral context by detailing what information is returned and the scope of the state it reports, though it does not describe potential staleness or refresh semantics.

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, well-structured sentence that front-loads the core action ('Returns the current toolkit state') and then lists the specific components. Every word contributes meaning, with no redundancy or filler.

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, no-parameter, read-only tool, the description fully covers what the agent needs to know: what the tool does and what the output will include. No output schema is present, but the description enumerates the key result components sufficiently for a tool of this complexity.

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 description needs to explain none; the baseline for 0 params is 4. The description adds no parameter information, but none 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 uses a specific verb and resource: 'Returns the current toolkit state' and enumerates exactly what is included (installed MCPs, connection status, connected accounts, catalog tool counts). This clearly distinguishes it from sibling tools like show_version, connect, and 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 strongly implies when to use the tool: whenever an overview of the toolkit state, installed MCPs, or connection statuses is needed. However, it does not explicitly mention alternatives or exclusion cases, such as 'use show_version for version-only info'.

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