SEFAZ CE DEC: Caixa Postal

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

The description discloses behavioral details beyond annotations, such as the token being non-expiring if set via config versus session-only if pasted, and that calling with no arguments returns a link. It clarifies the idempotentHint by explaining that authentication can be set or updated. No contradiction with annotations; it complements them well.

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 at three sentences, but the second sentence is long and might be clearer with bullet points. However, every phrase carries essential information—the authentication flow is fully explained without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with a single optional parameter, the description covers both call patterns (with and without token) and the recommended permanent configuration. It omits error handling or edge cases, but these are out of scope given the low complexity and lack of output schema.

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 coverage, the description fully compensates by explaining the 'token' parameter as a JWT, how to pass it ({ token: "<jwt>" }), and that omitting it triggers a link response. This adds significant meaning beyond the minimal schema definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to authenticate by logging in and providing an access token. It distinguishes itself from siblings by focusing on authentication flow, with specific actions like 'log in in the browser' and 'call with { token: ... }'. The resource (authentication) and verb (get token, store) are explicit.

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 when-to-use guidance by explaining two usage modes: no-arg for a link and token-based for session login, plus a recommendation to use a config header for permanent access. It implies when to use it (when needing authentication) but does not explicitly name alternative tools like 'connect' for comparison, though the context is 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 already indicate read-only, non-destructive, idempotent behavior. The description adds valuable behavioral details about what happens in the all-connected state versus the missing-credentials state, including the presence of authenticated and pending fields in the response.

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 and wastes no words. It front-loads the primary purpose and then efficiently explains the two relevant response 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?

For a zero-parameter, read-only status tool, the description covers the important return outcomes: all connected versus missing credentials. Even without an output schema, it tells the agent enough about authenticated, pending, and connect_url to invoke the tool and interpret the result.

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 coverage is 100%, so the baseline of 4 applies. The description still communicates what the response will contain across different provider connection states, which is the key semantic information an agent needs.

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, with a specific first sentence identifying the resource and verb. It also distinguishes itself from sibling tools like authenticate by focusing on status checking rather than establishing a connection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is used to check whether providers are connected and to obtain URLs when credentials are missing. While it does not explicitly name alternatives like authenticate, the conditional scenarios make the appropriate use context clear and actionable.

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 readOnly=false, openWorld=true, no idempotency, and no destructiveness, but the description goes beyond by explaining side-effects: writes require owner/admin, invoke runs tools even if not installed without bloating the tool list, and returns connect/checkout links for auth or payment. It also flags installed_in_toolkit vs installed_in_workspace. A small gap is not specifying exact behavior for resume or cancel_comment, but overall it discloses key behavioral traits.

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, around 250 words, covering 14 actions in a single block paragraph without bullet points or clear separation. While comprehensive, it sacrifices navigability and structure. For a tool with this many capabilities, a structured list would improve clarity. The length is justified but not optimally organized.

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 complexity (14 actions, 23 params, no output schema), the description gives a good high-level overview and highlights key flows (search→describe→invoke, billing, prompts), but it omits details about return formats, error handling, and many parameter purposes. It is adequate for orienting an agent but not fully complete for nuanced usage.

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 23 parameters and 0% schema description coverage, the description partially compensates by explaining the action enum and the core flow (e.g., action=search → describe → invoke with tool_id and arguments). However, it leaves many parameters unexplained, such as limit, conversation, immediate, prompt_vars, prompt_targets, and request_details. It adds meaning to primary params but not exhaustively, so it merits a middle score.

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 is the official marketplace catalog of MCPs/tools and the mechanism to run them, covering capability requests like finding an MCP or asking about a CPF. It differentiates itself from sibling tools by detailing its sub-actions (search, describe, invoke, install) and contrasting with list_tools and prompt-library operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use each action: use install for permanent addition to the toolkit, prefer invoke for one-off runs, use list_tools for currently callable tools, and subscribe/cancel for billing. It also names alternatives (e.g., report_bug, request_mcp) and specifies conditions like requiring admin for writes, clearly steering 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 include idempotentHint:true and readOnlyHint:false, but the description adds value by instructing to include the conversation array for reproduction, which is beyond the annotations. It does not contradict any annotation; it provides helpful behavioral guidance.

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, clear sentence that front-loads the purpose and includes a specific instruction. There is no fluff or redundancy; every word 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's simplicity, three parameters, and no output schema, the description is sufficiently complete. It explains the core action and the key reproduction step, and the siblings are unrelated, so no confusion exists. Some parameter details are left to the schema, but the schema lacks descriptions, so a slightly higher detail level could improve completeness—still adequate.

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. It explicitly mentions the 'conversation' parameter and implies 'message' is the bug report, but does not explain the 'context' parameter. It provides some semantic meaning but not full coverage of all 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's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb and resource, and distinguishes it from siblings (authenticate, 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 gives clear context for when to use the tool—when reporting bugs, missing features, or feedback—but does not explicitly mention alternatives or when not to use it. Since no sibling tool serves this purpose, the guidance is adequate without exclusions.

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 useful behavioral and compliance context beyond the annotations: data comes from official Brazilian sources, is not confidential, the client retains LGPD responsibility, and queries are paid. It does not contradict the read-only/idempotent hints.

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, front-loaded with the core purpose, and each sentence adds distinct useful information: purpose, hosting/payment, data source/classification, and LGPD responsibility.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with five parameters and no output schema, the description gives enough domain context but leaves important invocation details uncovered: which identifier is required, what the response contains, and how the PKCS#12 credentials should be used.

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?

None of the five parameters are explained in the description, and schema description coverage is 0%. Names like pkcs12_cert and pkcs12_pass are partially self-explanatory, and SEFAZ context hints that cnpj/ccm are identifiers, but ccm and ignora_nao_lidas remain unclear, which is risky 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 clearly states a specific action: consulting SEFAZ CE DEC Caixa Postal in an official source. It does not distinguish from sibling tools, but the sibling tools are mostly platform-level utilities, so the target resource is clear enough.

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 communicates practical context: it is hosted by the platform, does not require platform credentials, and is paid per query with prepaid credit. It does not explicitly say when to prefer this tool over alternatives or when not to use it, but the intended context is reasonably implied.

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, which covers the safety profile. The description adds no behavioral details beyond the resource being queried, but it does not contradict 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, direct sentence with no filler or redundant wording. Every word contributes to the 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 zero-parameter, read-only, idempotent version-query tool, this description is fully sufficient for an agent to select and invoke it correctly. No output schema is present, but the expected content is implicit in the word 'versions'.

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 zero parameters, so no parameter explanation is needed. The baseline of 4 for zero-parameter tools 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 uses a specific verb ('Show') and names a concrete resource ('current MCP platform and adapter versions'). It is clear, though it does not explicitly differentiate itself from the sibling 'toolkit_info', which may also provide informational output.

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 use case is implied: an agent should call this when version information is needed. However, the description does not explicitly state when not to use it or mention alternatives such as 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 declare readOnlyHint, idempotentHint, and destructiveHint false, so the agent knows this is a safe read. The description adds concrete context about what information is returned, which goes beyond the empty schema. No contradiction; it reinforces the annotation's safety profile.

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 that lists all output components without any filler. It is front-loaded with the verb and resource, making it immediately scannable.

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 no parameters and no output schema, the description fully covers what the tool does and what it returns. The list of contents (installed MCPs, connection status, accounts, catalog tool counts) is sufficiently detailed for an agent to decide if this is the right 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?

There are no parameters, and the schema is empty with 100% coverage by default. The baseline for zero parameters is 4, and the description appropriately focuses on output rather than inputs, adding no unnecessary 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 uses a specific verb 'returns' and clearly names the resource 'current toolkit state', then enumerates the exact elements returned (installed MCPs, connection status, accounts, catalog tool counts). This is unambiguous and distinguishes it from sibling tools like show_version, which likely only reports 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 implicitly tells the agent when to use this tool: whenever you need a summary of the toolkit's current state. It does not explicitly mention alternatives or when not to use it, but for a zero-parameter informational tool this is clear enough. It could name show_version as the alternative for version-only queries.

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