SINTEGRA: MS

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

Goes beyond the annotations (readOnly=false, idempotent=true) by explaining the flow: it returns a link when called with no args, and accepts a JWT token for session login. It also mentions the permanent option via config, which is not in annotations. 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 a single paragraph but is informative. It could be more structured (e.g., bullet points) but is not overly long. It front-loads the purpose and then gives usage details. Slightly rambling but still concise enough.

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 main usage modes and gives context on how to authenticate (browser, token). It doesn't mention what the response looks like, but for an authentication tool that sets a token, the reader likely knows it returns success/failure. Provided there is no output schema, the description 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?

Since the schema has no description for the 'token' parameter and coverage is 0%, the description fully compensates by explaining that `token` is the JWT to authenticate, and how to use it. No other parameters exist, so the single parameter is well-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 authenticates by logging in via browser and obtaining an access token From the context, it distinguishes itself from sibling tools like 'connect' and 'toolkit_info' by being specifically about authentication and token management.

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 when-to-use guidance: explains the permanent config approach vs session-only token paste, and gives exact call patterns (with/without token). It clearly instructs the agent on how to invoke the tool in different scenarios, making it obvious when to use this tool versus 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 readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral detail about response states, including authenticated:true, empty pending[], and connect_url behavior, which goes 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 two sentences, front-loaded with the core function, and every phrase adds meaning. It efficiently covers the main purpose and key conditional outcomes without unnecessary detail.

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, the description fully explains the relevant return values for both connection scenarios. The zero-parameter tool is simple, and the description provides enough context for an agent to know what to expect from the response.

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 schema description coverage is 100%, so there is no parameter burden to compensate. The baseline of 4 applies because parameter semantics are not applicable and the description still clarifies the return behavior.

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 with a specific verb and resource: 'Returns connection status and URLs.' It also distinguishes itself from the sibling tool 'authenticate' by focusing on status reporting rather than authentication 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?

The description provides clear context about when different results occur ('When all providers are connected...' vs 'When credentials are missing...'), which implies usage for checking connection state. It does not explicitly name alternatives or exclusions, but the read-only status-check context 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?

Despite having annotations (readOnlyHint=false, openWorldHint=true), the description adds enormous value: invoke's side-effect of running tools without installing, the connect link for missing credentials, the checkout/top-up link when the wallet is empty, and the permission requirement that writes need workspace owner/admin. It also explains the one-off install behind invoke and the prompt library's no-login share links. No contradiction with annotations. Annotation Contradiction: false.

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?

Every sentence earns its place and there is zero fat, but it is one giant wall-of-text paragraph with no structural hierarchy. Helpful typography (CAPS for 'KEY', 'PERMANENT') partially compensates, and the information density is high, yet the reader would benefit enormously from sentence-per-action breaks. It is efficiently written but not 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?

For a tool of this complexity (14-action enum, 23 parameters, no output schema, no parameter descriptions), the description is remarkably whole. It covers the full state machine (search→describe→invoke), failure/recovery paths (connect/checkout links with retry), permission model, the distinction between one-off invoke and permanent install, list_tools semantics, billing operations, issue reporting, and the entire prompt library subsystem. This is strong coverage for a facade tool of this scope.

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 carries the full burden and mostly delivers: it explains the action enum semantics thoroughly, clarifies tool_id, arguments, prompt_slug, and the relationship between action values. It loses a point because some non-obvious parameters (report_context, conversation, limit/query semantics, cancel_reason behavior) are left unexplained, and the description could not feasibly cover all 23 params given the length — but the critical action-cluster params are well handled.

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 opens with a precise job statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It specifies the exact capability domains ('find an MCP that does X', 'consulta um CPF') and differentiates each sub-action (search vs. describe vs. invoke vs. install). It clearly distinguishes itself from siblings by framing itself as the catalog+runner while siblings like authenticate/show_version are utilities.

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?

Explicit, prescriptive guidance throughout: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It contrasts with alternatives ('To filter by user/workspace, use search_calls_extensive' style clarity through 'list_tools lists what is callable right now'), and it even documents the retry flow after auth/payment links are opened. This is model-guidance gold.

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 indicate non-read-only, non-destructive, and idempotent, but the description adds no extra behavioral context (e.g., that it creates a ticket, sends an email, or returns a confirmation). It doesn't contradict annotations, but it also doesn't disclose side effects or expected outcomes beyond the action itself.

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 a brief instructional note. No fluff, no redundancy. Highly 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?

The tool has no output schema and the description does not explain what happens after reporting (e.g., returns a ticket ID, gives confirmation, is fire-and-forget). It also doesn't mention whether authentication is needed, though sibling 'authenticate' exists. The description covers the 'what' but not the 'outcome' fully.

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 no parameter descriptions (0% coverage). The description clarifies that 'conversation' should contain recent messages for reproduction, which adds value. However, it doesn't explain the required 'message' field or 'context' field, leaving the agent to guess their precise roles. Partial compensation for the schema gap.

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?

Clear, specific verb+resource: 'Report a bug, missing feature, or send feedback.' The tool's purpose is unambiguous, and it stands apart from all sibling tools (auth, connect, marketplace, etc.), which are unrelated.

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 context for one parameter ('Include the conversation array... for reproduction') but lacks explicit guidance on when to use the tool, prerequisites, or alternatives. Since no sibling tool competes, the gap is minor, but it could state 'Use this when the user reports an issue.'

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 false, covering the safety profile. The description adds value by specifying exactly what is shown (MCP platform and adapter versions), which goes beyond raw annotations. However, it does not describe the output format or any other behavioral details, but for a simple read-only tool this is sufficient.

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 that fully communicates the action and scope. No wasted words; it is front-loaded and 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 simplicity of the tool (no parameters, no output schema, strong annotations), the description is complete. It tells the agent exactly what the tool does, and the annotations cover safety aspects. There are no gaps that need further explanation.

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 schema description coverage is 100% (empty schema). Per the rubric, with 0 params the baseline is 4. The description adds no parameter details because there are none, so the baseline 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 it shows the current MCP platform and adapter versions, using a specific verb ('Show') and resource ('versions'). It distinguishes from siblings like 'toolkit_info' by focusing specifically on versions, and the name reinforces the purpose.

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 does not explicitly mention when to use this tool versus alternatives or any exclusions. While the context is clear from the name and description, there is no guidance on when not to use it or how it differs from potentially overlapping tools like '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?

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to re-cover safety. It adds genuinely valuable context: the pay-per-query cost model with prepaid credit, the fact that no platform credentials are needed, data sensitivity (not confidential, same as available to citizens), and LGPD obligations for the client as data controller. This is exactly the kind of beyond-annotation context (auth needs, cost, legal) the rubric rewards.

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 run-on stretch of colon and comma-separated clauses cramming in purpose, hosting model, payment terms, data sensitivity, and legal responsibility. Every sentence does carry information, but the most important information (what SINTEGRA MS is and what it returns) competes for attention with billing and legal disclosures. It's acceptable but not tight — it reads more like a terms-of-service blurb than an API description.

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 (2 plain string params, no output schema, no nested objects, no enums), the description covers the essentials: purpose, what data it accesses, and the legal framing around that data. The annotations handle safety profiling. However, it omits practical details a caller would want, such as what kind of results come back, what happens on a missing/invalid IE/CNPJ, or whether the result varies from the citizen-facing version in any way. Serviceable, with room to grow.

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 2 parameters (ie and cnpj), the description carries the full burden of explaining parameters but says nothing about them. A caller unfamiliar with 'ie' (Inscrição Estadual) or how it relates to 'cnpj' would get zero help. The description was the only place to clarify these parameters and entirely missed the opportunity — an especially damaging gap for a query tool where the parameters are the 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 clearly identifies a query operation against SINTEGRA MS ('consulta em fonte oficial') — a specific verb ('consulta') and resource (SINTEGRA MS, a known Brazilian state taxpayer database). It distinguishes itself from the sibling tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) by being the only data-query tool. It loses a point because the core purpose is somewhat diluted under pricing and LGPD compliance language rather than crisply stating it queries Brazilian state tax registration data.

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?

There is no explicit guidance on when to use this tool versus alternatives, and no when-not-to-use instructions. The description provides context — hosted platform, no platform credentials, prepaid credit, queries official non-confidential sources — but never explains how a caller should decide to invoke this over another tool. The compliance framing ('o cliente é o controlador dos dados') implies conditions for use but doesn't deliver actionable selection 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool is clearly safe. The description enriches this by detailing what data is returned (installed MCPs, statuses, accounts, counts), adding behavioral context without contradicting 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, front-loaded sentence that conveys all essential information without any redundancy. It is concise and to the point.

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 output schema, so the description carries the burden of explaining return values. It lists all key fields (installed MCPs, connection status, accounts, catalog tool counts), making it complete for the tool's 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 has zero parameters, so the schema fully covers parameter semantics. With 0 parameters, the baseline is 4, and the description adds no parameter info because none is needed. This 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 the tool's purpose: it returns the current toolkit state with specific components (installed MCPs, connection status, connected accounts, catalog tool counts). This is a specific verb-resource combination and distinguishes it from siblings 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 provides no guidance on when to use this tool versus alternatives. It does not mention any context, exclusions, or alternative tools. Usage is only implied by the tool's purpose, so it lacks explicit direction.

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