SEFAZ AL: NFC-e

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

Beyond annotations, the description discloses key behaviors: permanent non-expiring connection via config header vs session-only login via pasted token, and that calling with no args returns a link. Annotations (idempotentHint, destructiveHint) are consistent with this, but more detail on session lifespan or return value would be valuable.

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 organized with a clear purpose statement and then two method options, each on separate clauses. It's slightly verbose with the 'MCP.AI for IDE agents' prefix and wordy phrasing, but every sentence adds necessary 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?

Given the simple one-parameter schema and no output schema, the description covers essential usage scenarios, token handling, and link generation. Missing details like exact return values or error conditions, but adequate for an authentication tool with good annotations.

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 provides no description for 'token' (0% coverage), but the description compensates fully: 'call with { token: "<jwt>" }' explains the token's meaning and format, and states it's optional (no args case). This gives complete semantic guidance.

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: logging in to MCP.AI for IDE agents via browser and access token. It uses a specific verb ('log in') and resource, and distinguishes from siblings like 'connect' by focusing on authentication flow.

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 each method: 'Best: add it to this server's config as a header' for permanent connection, or 'paste it here for a session-only login'. Also explains calling with no args to get the link, giving clear usage context and 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 establish readOnlyHint=true and idempotentHint=true, indicating a safe getter. The description supplements this by detailing the two possible response states (authenticated:true with empty pending[], or connect_url with per-install URLs), which adds valuable behavioral context beyond the 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 two concise sentences, front-loaded with the primary function. The second sentence provides conditional details efficiently without redundancy. Every word contributes to understanding the tool's output and states.

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), the description is complete. It covers both normal and fallback scenarios, making the tool's behavior fully predictable. The annotations cover safety, so no further context 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?

The tool accepts zero parameters, so the input schema provides no semantics to clarify. The description appropriately focuses on output behavior, and since schema coverage is 100% (trivial), the baseline for zero-parameter tools applies. No additional parametric explanation 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: 'Returns connection status and URLs.' This is a specific verb+resource combination that distinguishes it from sibling tools like 'authenticate' or 'toolkit_info,' which deal with different concerns. The elaboration on the two output states (all connected vs missing credentials) further clarifies its 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 provides clear context for when to use this tool—to check connection status—and implicitly indicates when it's relevant (e.g., diagnostic or initialization flow). While it doesn't explicitly state alternatives or when-not-to-use, the context is unambiguous given the sibling tool names, so the lack of formal exclusions is acceptable.

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 sparse annotations: invoke runs tools even without installing them, missing credentials return connect links, empty wallets return checkout/top-up links, and install/uninstall/subscribe/cancel are permission-gated. This goes well beyond the raw readOnlyHint/destructiveHint flags.

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 it has to cover many actions and behaviors. It is structured from the marketplace overview, to the core flow, to the key invoke behavior, to install-vs-invoke, to billing/writes, to the prompt library. The content is dense and only minally redundant, though a short list or explicit sections would have improved scannability.

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 complexity and the absence of an output schema, the description covers a lot: auth links, billing, install semantics, workspace integration, and prompt-library outcomes. It still leaves a few areas under-specified, such as the exact return formats for search/list_tools and the meaning of the resume action, so it is complete 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 description gives semantic meaning to key parameters like action, mcp_id, tool_id, and prompt-related slugs by explaining their roles in the core flow. However, schema description coverage is 0% and there are 23 parameters, so many parameters such as arguments, immediate, tier_slug, conversation, prompt_vars, and cancel_reason are left undocumented. The description compensates for the action-level drawn but not for the full schema.

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 clear, specific identity: "the in-platform catalog of every MCP/tool, AND the way to run them." It then explains the core search → describe → invoke workflow, which makes the purpose unmistakable and differentiates it from the more specialized 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?

It gives explicit usage guidance: search→describe→invoke for one-off runs, install for permanent toolkit additions, list_tools for currently callable tools, subscribe/cancel for billing, and request_mcp for unsupported needs. It also states clear authorization requirements for writes and says to prefer invoke over install for single/occasional use.

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 discloses that the `conversation` array should be included for reproduction, which is a useful behavioral note about the data sent. However, it does not mention external data transmission, authentication, or other side effects beyond what annotations already convey. Since annotations already indicate it is not read-only, the description adds slight value but does not fully elaborate on consequences.

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 concise sentences, front-loaded with the core purpose followed by a crucial parameter hint. No unnecessary words or repetition. Every word adds value.

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 with no output schema and straightforward purpose, the description covers the essentials. It lacks information about response/acknowledgment but that is not required given the absence of an output schema. The inclusion of a reproduction hint shows completeness for the primary use case.

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 needed to clarify parameters; it does so for the key `conversation` parameter by stating it should contain recent messages for reproduction. It does not touch `context` or `message`, but those are more self-explanatory. This proactive clarification lifts it above the baseline, though not perfectly comprehensive.

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') and a clear resource ('bug, missing feature, or send feedback'), making the tool's purpose unmistakable. It effectively distinguishes itself from siblings like 'show_version' and 'toolkit_info' by stating its function directly. The purpose is immediately clear even without additional 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 implies when to use the tool (when reporting bugs or feedback) but does not explicitly discuss when not to use it or compare it to alternatives like 'marketplace' or 'connect'. No exclusions or competing scenarios are mentioned, so it stops at implied usage.

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 context: it is hosted by the platform (no user credentials required), requires prepaid credit per query, and explicitly states the data is not confidential and subject to LGPD responsibilities. These details go beyond annotations and help the agent understand operational constraints and legal obligations.

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 and front-loaded, starting with the core purpose ('SEFAZ AL: NFC-e, consulta em fonte oficial') followed by operational and legal details. Every sentence adds value, and there is no fluff or redundant information. It is appropriately sized for the tool's simplicity.

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 one parameter and no output schema, the description covers the operational context (payment, credentials, LGPD) and states it queries information. However, it omits any explanation of what the parameter should contain and what the response will look like. While annotations cover safety, the lack of parameter details and output description leaves gaps for a first-time caller.

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 one required parameter 'nfce' (string) with 0% description coverage. The description does not explain what value the 'nfce' parameter should contain (e.g., access key, invoice number, format). While the parameter name is suggestive, no format or example is provided. The description fails to compensate for the lack of schema documentation, leaving the agent to guess the expected 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 states the tool queries NFC-e data from SEFAZ AL, an official Brazilian tax source. The verb 'consulta' (query) and specific resource 'NFC-e' from 'SEFAZ AL' leave no ambiguity about what the tool does. It also contrasts with generic sibling tools like 'authenticate' or 'show_version', making its unique purpose obvious.

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 operational context (hosted platform, prepaid credit, no credentials) but gives no explicit guidance on when to use this tool versus alternatives. There is no mention of use cases, exclusions, or when not to use it. Since sibling tools are generic platform utilities, the lack of alternatives is understandable, but the description still offers no decision-making support for tool selection.

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 well covered. The description adds minimal behavioral context beyond that, but for a simple version display, this is acceptable. 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 a single, concise sentence that front-loads the purpose. It contains zero waste and is appropriately sized for a simple tool with no parameters.

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, clear annotations), the description is complete enough. It states what the tool does and the annotations cover safety. The only minor gap is not specifying the exact format of the version output, but that is not critical for a version-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 doesn't need to explain parameters since there are none. The baseline for zero-parameter tools is 4, and the description adequately conveys the tool's function without needing 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 purpose: showing current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), which is clear and distinguishes it from sibling tools like 'toolkit_info' 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 usage for checking versions, but does not explicitly state when to use this tool versus alternatives like 'toolkit_info' or 'report_bug'. It provides no exclusions or alternative guidance, but the context is clear enough for a simple version query.

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 fully covered. The description adds useful context beyond the annotations by specifying exactly what state information is returned, which is especially valuable given there is no output schema.

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 redundancy or filler. Every phrase earns its place by clarifying either the resource or the contents of the returned state.

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, read-only introspection tool with strong annotations, the description fully covers the needed context: what the tool does, what it returns, and its non-destructive nature. No output schema exists, but the description provides enough detail about the return contents to guide correct use.

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 description bears no burden of explaining parameter meaning. The baseline of 4 is appropriate since no parameter semantics are needed 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 ('Returns') tied to a concrete resource ('current toolkit state') and enumerates exactly what is returned: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, 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?

The description provides clear context for when to call the tool—whenever an agent needs an overview of the toolkit's installed integrations and their health. It does not explicitly mention alternatives or when-not-to-use, but the purpose is distinct enough from its siblings that usage intent is broadly obvious.

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