SINTEGRA: SE

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

Discloses behavioral details beyond annotations, such as the distinction between a permanent non-expiring connection (config header) and a session-only login (paste token). This adds context about state and longevity, which aligns with the idempotentHint annotation without contradicting it.

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, run-on paragraph with parentheses and colon-heavy phrasing ('MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token.'), making it harder to parse quickly. It could be broken into clearer, front-loaded sentences without losing meaning.

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 one optional parameter and no output schema, the description covers the core invocation modes (with/without token) and setup options. However, it leaves implicit the actual return value (e.g., what 'get the link' returns) and error handling, which might be expected given the tool's simplicity.

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 provides no description for the 'token' parameter (0% coverage), so the description takes on the burden and explains its purpose ('call with { token: "<jwt>" } after the user pastes') and the no-args behavior. It effectively compensates for the lack of schema documentation.

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: to authenticate IDE agents by logging in via browser and using an access token. It mentions the resource (access token) and provides a direct action verb ('log in'), making the purpose unambiguous. It doesn't explicitly contrast with siblings like 'connect' or 'marketplace,' but the function is self-evident from the context.

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 call patterns: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link,' and distinguishes permanent vs. session-based use cases. However, it doesn't reference alternative tools or explicitly state when not to use this tool, so it partially meets the criteria.

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, idempotentHint, and destructiveHint, so the safety profile is known. The description adds useful behavioral detail about the conditional return values (authenticated:true with empty pending[] vs. connect_url and per-install URLs), which goes beyond simple schema info and helps set expectations.

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: first sentence gives the primary purpose, the next two cover the main conditional behaviors. Every sentence adds value 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?

The tool is simple with no parameters or output schema, so the description carries the burden of explaining return values. It covers the two most important scenarios (fully connected and missing credentials), but does not explicitly address partial connection states or error handling. This is a minor gap, but overall the description is sufficiently complete for an AI 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?

With 0 parameters, the description has no parameter semantics to explain. Following the rubric, a baseline of 4 is appropriate for zero-parameter tools, and the description adds no confusion.

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', using a specific verb and resource. It also explains the behavior for two distinct states (all providers connected vs. credentials missing), which distinguishes it from the sibling 'authenticate' tool that likely initiates a connection.

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 when to use this tool: to check connection status and obtain URLs. It does not explicitly mention exclusions or alternatives, but the context is clear enough for an agent to know not to use it for authentication. The sibling 'authenticate' serves as a natural alternative, though not explicitly referenced.

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 annotations only say readOnlyHint=false and destructiveHint=false, but the description reveals substantial behavioral details: invoke works without installing, may return a login/connect link or a checkout link, and writes (install/uninstall/subscribe/cancel) require workspace owner/admin. It also discloses side effects like 'without bloating the tool list' and the prompt library's anonymous-access 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 information-dense with zero filler — every sentence contributes — but the presentation is a single massive wall of text with minimal structural breaks. It front-loads the key concept well but sacrifices scannability, which is a real cost when an agent needs to quickly parse a decision.

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 15-action, 23-parameter function with no output schema and no parameter descriptions, the description covers the full complexity: the discovery-to-execution flow, the install-vs-invoke tradeoff, credential and payment edge cases, role-based write permissions, and the entire prompt library sub-system. It covers the hard parts that neither the schema nor annotations provide.

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, and it does for the most critical parameter (action) and the endpoints that matter (mcp_id, tool_id, prompt_slug). However, roughly a third of the 23 params (tier_slug, immediate, conversation, prompt_body, prompt_title, report_context, etc.) are never explicitly explained. It's a strong-but-not-complete compensation, so 4 is appropriate.

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 this is — 'the in-platform catalog of every MCP/tool, AND the way to run them' — and establishes the core flow: search discovers MCPs → describe returns profiles → invoke runs tools. It is specific about verbs and resources, and distinguishes against siblings (report_bug, request_mcp) with explicit contrasts like 'report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits.'

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?

Gives explicit guidance on when to use what: 'prefer invoke for a single/occasional use,' 'Use install only to make an MCP PERMANENT,' and 'list_tools lists what is callable right now.' It also names the exact alternative (request_mcp for new MCPs, report_bug for feedback), which is precisely the when/when-not/alternatives pattern the rubric rewards.

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 convey read/write safety, idempotency, and destructiveness. The description adds useful context by explaining the conversation array is for reproduction purposes, but it does not disclose what happens after reporting, expected side effects, or response behavior. This is acceptable given annotations, with only slightly added behavioral value.

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 with two purposeful clauses: one for the core purpose, one for a key input requirement. Both earn their place 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?

For a simple tool with three string parameters, the description is enough to know the overall intent and one important input. However, it leaves the 'message' parameter, 'context' parameter, and the unusual string-as-array for 'conversation' underspecified, and because there is no output schema, an agent might wonder about expected return data.

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 compensate, but it only clarifies 'conversation' (and only an array-like intention, while the schema type is string). It does not explain the meaning of 'message' as the required content or what 'context' represents. No syntax or format hints beyond the vague notion of an array.

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 ('Report') with explicit resource types ('bug', 'missing feature', 'feedback'), making the tool's purpose immediately clear. This distinct purpose and resource list also differentiates it from the sibling tools, none of which relate to reporting.

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 a clear contextual trigger: when a bug, missing feature, or feedback is needed. It also gives concrete invocation guidance ('Include the conversation array with recent messages'). It does not explicitly name alternatives or exclusion cases, but no sibling tool appears related to this function.

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 covered. The description adds the specific scope of reporting 'platform and adapter versions' but does not disclose any additional behavior such as output format or network dependencies. This is adequate but not rich.

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 with no filler. Every word contributes meaning, identifying the exact information the tool returns.

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, zero parameters, and strong annotations, the description is sufficient for an agent to select and invoke it. It could mention return format, but 'Show' strongly implies a readable version string. Overall, no critical information is missing.

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 parameter semantics are not applicable. The description correctly focuses on what the tool reports rather than on inputs, and the schema coverage is trivially complete.

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') with a clear resource ('the current MCP platform and adapter versions'). It accurately distinguishes this tool from siblings like toolkit_info and authenticate, which clearly serve different purposes.

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 when version information is needed, but there is no explicit guidance about when to use it versus alternatives. For a simple version-check tool, this is acceptable but not fully 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable context beyond these: the cost model (pay-per-query with prepaid credit), the data-source nature (same data available to citizens, non-confidential), and legal responsibilities (client as data controller per LGPD). This is meaningful additional behavioral disclosure about financial and legal 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?

Four sentences covering purpose, payment model, data nature, and legal compliance. It's compact but front-loads billing/legal boilerplate ('pague por consulta com crédito pré-pago', LGPD responsibilities) before the functional core. The first sentence does establish the main function, but the third and fourth sentences add legal disclaimers that feel like compliance copy rather than functional guidance.

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?

No output schema exists, and the description never addresses what the caller receives (return format, pagination, error behavior). The three parameters are wholly undocumented. For a pay-per-query tool with cost implications, the absence of any output/response description and any parameter-usage guidance leaves significant gaps. The payment context is described but the core mechanics of querying and results are not.

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 the description provides zero information about the three parameters (ie, cpf, cnpj). The description doesn't clarify that these are likely a one-of set (query by one identifier only), doesn't explain what 'ie' stands for (Inscrição Estadual), doesn't provide formatting guidance (masking, length), and doesn't note that none are required per the schema. No compensation for the 0% 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 states this is a SINTEGRA SE consultation against official Brazilian sources ('consulta em fonte oficial'). The verb 'consultar' in the name plus 'consulta' in the description makes the action clear. It doesn't explicitly contrast with sibling tools, but those (authenticate, connect, marketplace, etc.) are infrastructure tools with no apparent overlap, so differentiation isn't needed. Clear purpose, specific resource identified.

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 contextual usage information: no platform credentials needed, pay-per-query with prepaid credit, and LGPD responsibility for legitimate purpose. However, it gives no explicit when-to-use vs. when-not-to-use guidance, no mention of prerequisites, and no indication of what distinguishes this from potential alternative tax-data tools. The information present is useful but implicit rather than directive.

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 destructiveHint=false. The description adds valuable context beyond annotations by specifying exactly what information is returned (installed MCPs, connection status, accounts, catalog tool counts). It does not contradict annotations and provides meaningful behavioral detail.

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, tightly worded sentence that states the purpose and key outputs without any fluff or redundancy. Every phrase contributes to understanding the tool's functionality, making it highly efficient.

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) and rich annotations (readOnly, idempotent, non-destructive), the description fully covers what the tool does and what it returns. It provides sufficient detail for an agent to invoke it correctly, and no additional context about error handling or side effects 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?

There are zero parameters, so the baseline per rubric is 4. The schema description coverage is 100% since there are no parameters to document. The description correctly avoids mentioning parameters, as none exist, and therefore adds no confusion.

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 the toolkit state, enumerating the specific data (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb ('Returns') and resource ('current toolkit state'), which distinguishes it from siblings like 'show_version' or 'marketplace' that target different aspects.

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 the state of the toolkit but does not explicitly state when to use it versus alternatives like 'show_version' or 'marketplace'. No exclusions or alternative tool names are provided, so the agent must infer the context.

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