SEFAZ AL DEC: Caixa Postal

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

The description discloses key behavioral aspects: it is a read/write operation (non-readOnly, hence annotation readOnlyHint=false is consistent), but it is idempotent and non-destructive (matching annotations). It explains the side effect of initiating a browser login and the token handling. It adds context that calling with no args yields a link, and that the token is a JWT, which is beyond what annotations alone provide. 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 paragraph that is informative but not overly long. It front-loads the primary purpose and then provides usage details. It earns its sentences by explaining both login modes and the config option. It could be slightly more structured with bullet points, but it remains concise and readable, so no points deducted heavily.

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 of moderate complexity with one optional param, no output schema, and no nested objects. The description covers the workflow thoroughly, including the alternate config approach and session-only login. It addresses the necessary user interaction (paste token) and the onus on the agent. Given the simplicity, the description is complete for an agent to correctly invoke it without additional 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?

The input schema has only one parameter, 'token', with no description. The tool description provides substantial meaning: the token is a JWT access token pasted by the user, and it is optional. This goes beyond the schema's bare type and gives the agent the necessary context for how to populate the parameter appropriately. Though schema coverage is 0%, the description compensates well.

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 an IDE agent by either providing an access token or obtaining a login link. It specifies the target audience ('IDE agents (Cursor, etc.)') and the resource (authentication for the MCP server). It distinguishes itself from siblings like 'connect' and 'toolkit_info' by focusing specifically on login/authentication.

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 instructions on when to use this tool: after the user pastes a token, or with no arguments to get a login link. It also explains the alternative of adding the token to the server's config for a permanent connection, contrasting it with the session-only login via auth. This clear guidance helps the agent decide when and how to invoke the 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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful behavioral nuance by disclosing the two main response states: fully connected, and missing credentials with connect_url and per-install URLs. This goes beyond what annotations provide, though it doesn't detail partial-connectivity 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 two sentences, front-loads the primary purpose, and then delivers the key conditional outputs. Every clause adds value and there is no filler, tautology, or unnecessary 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 simple, zero-parameter status tool, the description covers the main states and return fields. It leaves some nuance unspecified (e.g., exact contents of pending[], partial connection scenarios), but the overall picture is sufficiently complete given the low complexity and strong 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?

The tool has zero parameters, so the schema already covers everything. With no parameters, the baseline is 4, and the description doesn't need to add parameter-level detail; it correctly focuses on output 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 uses a specific verb+resource: 'Returns connection status and URLs.' It further clarifies the purpose by describing condition-dependent outputs (authenticated:true with empty pending[] vs connect_url), which distinguishes it from sibling tools like authenticate and 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 usage context is implied: the agent would call this to check connection status. However, it never explicitly states when to use connect versus authenticate or other siblings, and it provides no exclusions or alternative-tool guidance. This is a clear but not explicit usage signal.

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 significant behavioral context that annotations do not: invoke runs tools without adding them to the toolkit, auth/payment failures return connect or checkout links, and write actions require owner/admin access. This goes well beyond the provided annotations and clearly sets expectations for side effects.

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 longer than average, but justified for a tool that dispatches 14 different actions across MCPs and prompts. It is front-loaded with the core flow and punctuated with caveats and explicit distinctions. A minor issue is the inclusion of a non-English word and a few multi-embedded clauses that slightly hurt readability.

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, the description provides strong contextual completeness: core flow, permission requirements, edge cases like missing credentials and empty wallet, and alternatives for permanent vs one-off execution. It does not exhaustively document every parameter or output format but gives enough context for correct tool selection and invocation in most cases.

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 takes on substantial responsibility. It explains the key action parameter enum and the core action-specific parameters like query, mcp_id, tool_id, and arguments, and the invoke flow. However, some parameters such as immediate, tier_slug, resume, and prompt_targets remain unexplained, leaving partial gaps despite the strong overall 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 clearly defines the tool as the official MCP.ai marketplace: a catalog of MCP/tools and the mechanism to run them. It explicitly names the core actions (search -> describe -> invoke) and differentiates from related tools by framing itself as the in-platform discovery and execution layer.

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 strong usage guidance: when to use search, describe, invoke, install, list_tools, subscribe, request_mcp, and the prompt library. It explicitly says to prefer invoke for a single/occasional use and install only when an MCP should be permanent within the active toolkit.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds that the conversation array should be included for reproduction, which is useful context. However, it does not detail side effects (e.g., whether a report is actually submitted) or any auth requirements, so it only partially supplements the annotation 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?

The description is two sentences, front-loaded with the purpose, and includes a practical note about the conversation array. Every sentence earns its place, with no redundancy or 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?

The tool is simple (3 string params, no output schema, no nested objects), but the description leaves gaps: it does not explain the 'context' parameter, what happens after reporting (e.g., confirmation), or any prerequisites (e.g., authentication). Given low parameter coverage and no output schema, the description is not complete enough for an agent to use effectively.

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%, so the description must explain each parameter. It only hints at 'conversation' (the array with recent messages) and implicitly covers 'message' as the report content, but 'context' remains unexplained. This is insufficient for a 3-parameter tool with no schema descriptions.

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 ('report') with a clear resource (bug/feature/feedback). It is distinct from sibling tools like 'authenticate' or 'marketplace' by its functional focus.

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 (when you encounter a bug or want to provide feedback) but does not explicitly state when not to use it or mention alternatives. No exclusions or alternate tools are referenced, so guidance is only 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?

The description adds value beyond the annotations by disclosing that the tool requires prepaid credit (cost), does not require platform credentials (but does require a PKCS12 certificate), accesses non-confidential data, and places LGPD responsibility on the client. These are meaningful behavioral traits not covered by the readOnlyHint, idempotentHint, or destructiveHint 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 that begins with the purpose and then provides operational details (payment, credentials, data classification). It is concise without excessive length, though the LGPD legal note adds some length without directly aiding tool selection or invocation. Overall, it is well-structured and front-loaded.

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 three parameters (two required) and no output schema. The description explains the general purpose and some operational constraints, but it does not clarify the required certificate parameters, the meaning of 'ie', or what the response contains. This leaves the agent without enough information to invoke the tool correctly or interpret results, making the description incomplete for a functional 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?

The schema has no descriptions, and the description does not explain any of the three parameters (ie, pkcs12_cert, pkcs12_pass). It mentions 'sem credenciais da plataforma' (no platform credentials), which is ambiguous and does not clarify that the certificate and password are required for user authentication or what 'ie' refers to. With 0% schema coverage, the description fails to compensate, leaving the agent without parameter 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 states the tool is for consulting 'Caixa Postal' (postal box) information from official Brazilian sources. It clearly identifies the verb (consulta) and the resource (Caixa Postal), and it is distinct from sibling platform tools like authenticate or connect. However, it does not specify what exact postal box data is returned or how it relates to SEFAZ AL DEC specifically, so a small gap remains.

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: no platform credentials needed, pay-per-query with prepaid credit, and data is public. It implies when to use this tool (for querying official Brazilian data) but does not explicitly state when not to use it or compare it to alternatives. Since there are no sibling data-query tools, the exclusions are implicit, yet the guidance is still minimal.

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 covered. The description adds the 'current' aspect and specifies that both platform and adapter versions are reported, but it does not describe the return format or potential edge cases. 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, front-loaded sentence that directly states the tool's purpose with no filler or redundant information. Every word contributes to understanding.

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, simple informational tool with strong annotations, the description is complete enough for an agent to select and invoke it correctly. No complex inputs, side effects, or alternatives need to be explained.

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 description coverage is 100%, so there is no parameter information for the description to add. The baseline of 4 applies because no parameter semantics are 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 uses a specific verb ('Show') and a clear resource ('the current MCP platform and adapter versions'), making the tool's purpose unambiguous. It is distinct from sibling tools such as authenticate or toolkit_info, which do not focus on version 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?

Usage is implied: call this tool when you need version information for the MCP platform and adapters. There is no explicit when-not-to-use guidance or comparison with alternatives, but the narrow scope makes misuse unlikely.

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 covered. The description adds what information is returned, which is useful context beyond annotations. However, it does not disclose any additional behavioral nuances (e.g., whether results are cached, network calls involved, or error handling). With annotations doing the heavy lifting, 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 a single, dense sentence that front-loads the primary action ('Returns the current toolkit state') and then lists the specific components. Every phrase adds value; there is no fluff or redundancy. It is exceptionally 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 no output schema exists, the description carries the responsibility of conveying what the tool returns. It does so by enumerating the four key pieces of state: installed MCPs, connection status, accounts, and catalog tool counts. This is adequate for a simple info-retrieval tool, though it could additionally note whether the output is a flat list or nested structure. The tool's simplicity means this level of detail is sufficient, 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 tool has zero parameters, so the schema is trivially complete (100% coverage). Per the rubric, a baseline of 4 applies for 0 parameters. The description adds no parameter-specific semantics (none needed), but this does not detract—the baseline stands because there is no parameter burden to compensate for.

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') plus a clear object ('current toolkit state') and enumerates the actual content (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like show_version (version info) and connect (establishing connections), leaving no ambiguity about the tool's function.

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 inspecting the toolkit's current state, which is the natural pre-check for actions like connecting or authenticating. However, it does not explicitly state when to use it over alternatives (e.g., show_version) nor any exclusions. The purpose is clear enough for context, but lacks explicit guidance.

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