SEFAZ RO: NFC-e Resumida

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

The description discloses important behavioral aspects: the 'permanent, non-expiring' nature of the config-based auth and the 'session-only' semantics of token passing. It also hints at side effects (changing authentication state). Annotations already mark idempotentHint=true, which aligns; no contradiction. Slightly more could be said about token revocation or security, but the key behaviors are transparent.

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 and runs on, mixing instructions for the agent, the user, and the implementation. It packs a lot of information into two long sentences, which could be better organized (e.g., bullet points). Still, every detail serves a purpose, and there's no fluff, but it's not the most readable. A 3 reflects adequate but not exemplary 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?

For an authentication tool, the description covers the main flows (permanent vs. session, with/without token) sufficiently. It explains how to obtain a token and the persistence trade-offs. It does not explicitly handle error cases (e.g., invalid token) or mention timeouts, but given the tool's simplicity and lack of output schema, it's reasonably complete. The sibling list includes 'connect' and 'marketplace', and while not explicitly contrasted, the description doesn't confuse them with authentication.

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 input schema provides only a parameter name 'token' with no description or type constraints, yielding 0% schema coverage. The description compensates fully by explaining that 'token' takes a JWT pasted by the user and that omitting it returns a login link. This exactly addresses what the parameter means and how to invoke the tool, making it excellent despite the sparse 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 clearly identifies the tool as an authentication mechanism for MCP.AI, explaining it logs in via browser and uses an access token. It's specific about the resource (authentication) and the two modes (config header vs. session token). However, it doesn't explicitly contrast with sibling tools like 'connect', so while purpose is clear, sibling differentiation is implicit.

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 usage context by explaining two paths: permanent (server config) and session-only (passing token) with a fallback to get a link. It implies when to use each method but doesn't explicitly state 'use this instead of X'. The guidance is practical and decision-oriented, earning a 4.

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 establish read-only, idempotent, and non-destructive behavior. The description goes beyond by disclosing the actual response structure—'authenticated:true and empty pending[]' when connected, and 'connect_url for the toolkit and per-install URLs' when credentials are missing. This adds valuable behavioral detail about conditional return values that annotations do not 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 exceptionally concise, consisting of exactly two sentences. The first sentence front-loads the core function, and the second elaborates on two specific conditional scenarios. Every word adds value, with no redundant phrasing or irrelevant 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 read-only status tool with no parameters and no output schema, this description is complete. It covers the primary success case (all providers connected), the partial-failure case (missing credentials), and the resulting next-step URLs. Given the low complexity and robust annotations, there are no significant gaps in 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?

With zero parameters, the schema is fully comprehensive (coverage 100%), and the description appropriately avoids adding unnecessary parameter information. The baseline score of 4 for zero-parameter tools is warrented, as there are no parameter semantics left unexplained.

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' with a specific resource, 'connection status and URLs', leaving no ambiguity about the tool's purpose. It further distinguishes itself from siblings by detailing conditional outputs (authenticated:true, pending[], connect_url) that clearly define its scope as a status-checking endpoint, setting it apart from tools like 'authenticate' or 'toolkit_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 implicitly communicates when to use this tool by stating exactly what it returns ('connection status and URLs') and contrasting conditions (all providers connected vs. missing credentials). However, it does not explicitly reference sibling tools or provide 'use instead of' exclusions, though the context of tool discovery makes the usage context quite clear.

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 are minimal (only readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false), so the description carries the burden and delivers richly: it discloses that 'invoke runs the tool pontualmente (one-off) without adding the MCP to the toolkit', the connect-link and checkout/top-up fallback flows for auth/payment, and that 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.' No contradiction with annotations — readOnlyHint=false is consistent with the documented write operations.

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 enormous wall of text. It is front-loaded with the core purpose (good), but then crams the action semantics, invoke behavior, auth/payment flows, permission requirements, and the entire prompt library into one dense unwieldy paragraph with no section breaks or scannable structure. For an agent parsing under time pressure, this forces a full read of ~250 words to extract the decision logic.

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 a very high complexity tool (14 actions, 23 params, no output schema), the description covers the critical decision points well: which action to pick, install vs invoke, write-permission requirements, and auth/payment fallbacks. But it leaves many parameters undocumented, and with no output schema it never describes return shapes (e.g., what search results look like, what invoke returns on success vs needing a connect link) — the behavioral hooks are there but 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% across 23 parameters, so the description must compensate. It explains the action enum meaningfully (search, describe, invoke, install, list_tools, etc.) and references tool_id, mcp_id, and arguments implicitly via the flow. But 17+ parameters (limit, query, message, immediate, tier_slug, prompt_body, prompt_vars, conversation, prompt_title, request_name, cancel_reason, cancel_comment, prompt_targets, report_context, prompt_category, request_details, prompt_description) receive no semantic explanation at all, leaving agents to guess formats and meaning.

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 opening states a clear scope: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It gives a specific verb+resource+scope and distinguishes itself from siblings (authenticate, connect, show_version, etc.). However, the tool is overloaded with 14 distinct actions across MCP operations AND a prompt library, making the true purpose diffuse and sprawling.

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?

Strong internal guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT in the active toolkit', 'list_tools lists what is callable right now', and the core search→describe→invoke flow is articulated. But it never contrasts against sibling alternatives — notably the marketplace's own report_bug action vs the sibling report_bug tool, and no 'when NOT to use marketplace' 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 declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, so the safety profile is already known. The description adds value by mentioning the conversation array for reproduction, but it does not describe any side effects, success/failure behavior, or whether a confirmation is returned. The description does not contradict annotations, so a score of 3 is appropriate—it adds some context but is not rich in 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 two sentences long, front-loaded with the purpose, and contains no fluff. It efficiently communicates the essence and one critical usage hint without padding. 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?

Given the tool has 3 parameters, no output schema, and no schema documentation for parameters, the description is too sparse. It does not explain what 'message' should contain, what 'context' is for, or what happens after reporting (e.g., confirmation, logging). For a write action with no output schema, the description should provide more guidance on expected behavior and return values. It is incomplete for effective tool invocation.

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 for explaining parameters. It only mentions 'conversation array' without explaining 'message' (the required param) or 'context'. The description gives minimal insight into parameter usage, leaving the agent guessing about the required message field. This is insufficient compensation for the zero 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 explicitly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a clear verb+resource (report + bug/feature/feedback) that distinguishes it from unrelated sibling tools like authenticate, connect, and marketplace. It is specific and actionable.

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 says 'Include the conversation array with recent messages for reproduction,' which gives contextual guidance on how to provide necessary information. Though it does not explicitly mention when not to use the tool or list alternatives, the sibling tools are unrelated, so exclusions are unnecessary. Clear context is provided, but no explicit 'when not to use' is stated.

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 signal read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond those hints: prepaid billing, lack of platform credentials, the data is the same as available to citizens, not confidential, and the customer is the LGPD data controller. This covers cost, access, and legal expectations without contradicting 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 compact paragraph with the core purpose front-loaded, followed by payment, credentials, and LGPD context. It avoids unnecessary length, though the LGPD clause is somewhat boilerplate and could be shorter without losing essential 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 one-parameter read-only tool, the description covers purpose, official source, payment model, and data-control responsibilities. However, with no output schema and no parameter format guidance, the return-value expectations and the exact nfce input requirement remain unaddressed.

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 input schema has 0% description coverage and the required 'nfce' parameter is only typed as a string with no explanation of format or expected value. The description only hints at the NFC-e domain but does not specify whether nfce is an access key, invoice number, or other identifier. This is a significant gap for 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 opens with 'SEFAZ RO: NFC-e Resumida, consulta em fonte oficial', naming the exact resource and operation: querying summarized NFC-e data from the official SEFAZ/RO source. This clearly distinguishes the tool from platform-level siblings like authenticate, connect, and marketplace.

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 clear operational context: hosted by the platform, no platform credentials required, pay per query with prepaid credit, and data comes from official Brazilian sources. It does not explicitly name alternatives or when-not-to-use, but the sibling list contains no competing data-query tools, so the guidance is sufficient.

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 idempotentHint=true, so the safety profile is clear. The description adds the specific output (versions) but doesn't disclose additional behavioral traits like response format or whether it requires connectivity, which is acceptable given the tool's simplicity.

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?

A single, concise sentence that front-loads the action and resource. No extraneous information, perfectly 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?

Given the tool has no parameters, no output schema, and clear annotations, the description fully captures what the tool does. The one-sentence description is entirely sufficient for an agent to understand and invoke it correctly.

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 is 4. The description correctly implies no input is needed, and the schema confirms this with no properties.

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' and resource 'versions', clearly stating the tool displays the current MCP platform and adapter versions. It distinguishes itself from siblings like toolkit_info by focusing on versions rather than general 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 the tool is for checking version information, but it doesn't explicitly state when to use it over alternatives. Given its simplicity and lack of sibling overlap, a baseline adequacy is present.

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, destructiveHint=false, covering the safety profile. The description adds valuable context by specifying exactly what the returned state includes (connection status, accounts, catalog tool counts), going beyond the annotations' hint that it's read-only.

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?

A single, well-structured sentence efficiently conveys the tool's purpose and the specific data it returns. 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?

The description sufficiently covers the tool's behavior for a simple, parameterless read-only tool. It lists the major areas of the state but doesn't specify formats or additional details. Given the simplicity and lack of output schema, this is adequate, though a touch more context (e.g., when the state might be empty) would round it out.

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 baseline is 4. The description adds no parameter information, but none is needed since the schema fully covers the (empty) parameter set.

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 verb 'Returns' and the resource 'toolkit state', enumerating specific components (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes itself from all sibling tools, none of which provide state information.

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 (when needing an overview of the toolkit), and no sibling tool offers similar functionality, so no exclusions are needed. However, it does not explicitly state 'use this to check state' or mention any prerequisites, so it stops short of perfect guidance.

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