SEFAZ PA: NFC-e

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

The description discloses key behavioral details: token input creates a session-only login, no args returns a login link, and permanent login should be handled via config rather than this tool. Any hits idempotent flag without contradiction; no destructive readOnly conflicts appear.

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 but not overly long, containing essential setup and invocation details. The flow from login in the browser, to config recommendation, to session-only call is logical and useful, though the opening audience phrase adds a little non-essential context.

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 one optional parameter and no output schema, the description covers the main invocation cases and their outcomes reasonably well. It leaves some detail implicit, such as exact return format or the meaning of 'link', but gives enough for an agent to call the tool correctly in typical workflows.

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 only a bare optional string token with 0% description coverage, so the description fully carries the burden. It explains the token is a JWT, how it is obtained, what it does when passed, and the meaning of omitting it—making the parameter semantics completely clear.

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 that this tool is for authenticating with MCP.AI for IDE agents, explaining that it can either produce a login link or accept a pasted JWT. It is more detailed and actionable than just 'authenticate', but it does not explicitly distinguish itself from the sibling tool '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?

It gives explicit usage guidance: prefer server config for a permanent non-expiring connection, use the tool for session-only login, and use either the token or no-args form depending on whether the user pasted a token. It does not name alternatives explicitly, but the permanent-vs-session distinction is a clear when-to-use guide.

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 clear. The description adds useful context about the return states (authenticated:true vs. connect_url) but does not disclose details like whether it makes network calls or how it determines provider connection status. With annotations covering the safety aspects, a 3 is appropriate.

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, and every sentence adds value. It is 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?

Given the tool has no parameters, no output schema, and annotations cover safety, the description is fairly complete. It explains the two possible return states and what they mean. It could be slightly more explicit about the exact structure of the response (e.g., fields like authenticated, pending, connect_url) but overall it is adequate for a status-checking 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 zero parameters, and schema description coverage is 100% (vacuously). The description explains the output semantics (authenticated:true and empty pending[] vs. connect_url and per-install URLs), which is valuable since there is no output schema. This compensates for the lack of 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 returns connection status and URLs, and explains the two possible states (all connected vs. missing credentials). It distinguishes itself from siblings like authenticate and show_version by focusing on status/URLs rather than performing authentication or showing version info.

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 (to check connection status and get URLs when credentials are missing) but does not explicitly state when not to use it or mention alternatives. It provides context about the two states but lacks explicit guidance on when to prefer this over authenticate or other tools.

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 the sparse annotations (not readOnly, not destructive), the description reveals key behaviors: invoke works on non-installed MCPs, credential/payment issues produce connect/checkout links that require user action, search/describe flag installation status, and writes require owner/admin. This is meaningful operational context not visible in 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 long but densely packed with must-know distinctions and edge cases. It front-loads the core marketplace flow and uses key terms like KEY and use install only to prioritize important behavior. It could be more scannable, but every sentence serves the agent's decision-making.

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 highly complex 23-parameter umbrella tool with no output schema and no parameter descriptions, the description provides a solid macro overview but omits many parameter semantics and a few sub-actions (e.g., resume, immediate behavior, report_bug details). It is substantially better than a minimal stub but not complete enough to invoke all cases correctly without additional probing.

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 there are 23 parameters, so the description bears full responsibility for parameter meaning. It explains the action-centric flow and mentions tool_id, prompts, and some fields, but leaves many parameters like limit, immediate, arguments, conversation, cancel_reason, report_context, request_details, tier_slug, and prompt_vars unexplained. This is insufficient for a 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 identifies the tool as the official mcp.ai marketplace/catalog and runtime, covering capability requests and discovery-to-invoke flow. It names specific sub-actions (search, describe, install, invoke, subscribe, prompt library actions) and thereby distinguishes its multi-purpose role from the narrower sibling 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?

The description offers explicit selection guidance: prefer invoke for single/occasional use, use install only to make an MCP permanent, use list_tools for what is callable now, and request_mcp when nothing fits. It also states write operations require workspace owner/admin, helping the agent decide whether to even attempt the call.

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 already declare idempotentHint=true and destructiveHint=false, indicating a non-destructive, repeatable operation. The description adds the reproduction context for the conversation input but does not disclose additional behaviors like submission targets, response format, or rate limits. 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 two sentences, no fluff. It front-loads the purpose before adding a usage 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?

For a simple reporting tool, the description covers the core purpose and a key reproduction requirement. However, it doesn't mention expected response or what `context` is for, and it relies on annotations for safety information. Overall adequate but not exhaustive.

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 descriptions for any of the three parameters. The description explicitly instructs to include the conversation array for reproduction, clarifying `conversation`, and implies `message` carries the report. However, `context` is unmentioned, and `conversation` is called an array while the schema types it as a string, leaving some 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 states 'Report a bug, missing feature, or send feedback,' clearly specifying the action and resource. This distinguishes it from 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 first sentence makes the use case obvious. The second sentence adds specific guidance: 'Include the conversation array with recent messages for reproduction.' No alternatives are mentioned, but none are needed given the distinct purpose.

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: no platform credentials needed, pay-per-query with prepaid credit, and that the client is the data controller under LGPD. This goes beyond the annotation basics and clarifies operational and legal 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 front-loaded with the purpose and packs useful info about hosting, payment, and LGPD into a few sentences. It is somewhat dense but every sentence carries distinct information, with no waste or repetition.

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 single-parameter query tool, the description covers purpose, payment, and data responsibility. However, with no output schema, it does not describe what the response contains, potential error cases, or any usage limits. It is adequate for a simple lookup but leaves room for the agent to guess on return format.

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 coverage is 0% and the description does not explain the 'nfce' parameter beyond the tool name. It mentions NFC-e as the subject but does not say the parameter is the NFC-e key/access key or provide any format or example. The agent must infer the meaning from the tool name alone.

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 'SEFAZ PA: NFC-e, consulta em fonte oficial', specifying both the resource (NFC-e via SEFAZ PA) and the action (consulta/query). It clearly distinguishes from sibling tools like authenticate or marketplace by focusing on the official tax document consultation.

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 on when to use the tool: it is hosted by the platform, requires no platform credentials, and payment is per consultation with prepaid credit. It also notes the data is non-confidential and subject to LGPD responsibilities, but does not explicitly mention alternatives or when not to use this tool.

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 already provide readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds specific detail about what is displayed (platform and adapter versions), which goes slightly beyond the bare semantics, but it does not disclose additional behavioral traits such as latency, error modes, or prerequisites. Since annotations cover the main concerns, a score of 3 is appropriate.

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 words. It perfectly conveys the tool's purpose in the minimum possible space, earning full marks for conciseness and structure.

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 extreme simplicity (no parameters, no output schema, read-only behavior already declared via annotations), the description fully covers the necessary context. It states what the tool does, and the annotations handle safety and idempotency. There is no missing information that would hinder an agent's ability to correctly select and invoke this 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 zero parameters, and the schema coverage is 100% (essentially no parameters to document). The description does not need to explain parameter semantics, so the baseline of 4 applies. The description correctly adds no redundant parameter details.

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 identifies the resource (platform and adapter versions), and it is easily distinguished from sibling tools like authenticate, connect, or report_bug, which have entirely 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 when to use the tool (when version information is needed) but does not explicitly mention alternatives or scenarios where it should not be used. For a simple, self-explanatory version-check tool, the usage context is reasonably clear from the description alone, but it lacks explicit 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 agent knows this is a safe read operation. The description adds detail about what the returned state contains, but does not disclose additional behavioral traits beyond what annotations already establish.

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 entire description is one focused sentence with the main verb and subject front-loaded. Every phrase adds information, with no filler or repetition.

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 zero-parameter complexity, the description fully specifies what the agent should expect in the return value. There is no output schema, but the description explicitly lists the important return categories, making it sufficiently 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 tool has zero parameters and schema description coverage is 100%, so parameter semantics are not a concern. The description appropriately needs no parameter details to be usable.

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'), identifies the resource ('current toolkit state'), and enumerates exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly differentiates it from sibling tools 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 this is the tool for inspecting overall toolkit health/status, but it does not explicitly compare it to alternatives such as show_version or marketplace. It provides enough context for basic selection but lacks explicit when-to-use or 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.