INCRA SIGEF: Detalhes de Parcela

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

Annotations already indicate idempotent and non-destructive behavior; the description adds valuable context about the permanent vs session-only distinction, the exact token format (JWT), and that calling with no args returns a link. It does not describe the response when a token is provided, but given the simple scope, this is acceptable.

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 paragraph that front-loads the purpose and then explains the two usage modes. Though it could be better structured with bullet points, every sentence provides necessary information and there is no padding.

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 one optional parameter, no output schema, and strong annotations, the description covers purpose, usage modes, parameter semantics, and behavior. The main gap is the lack of detail on what the tool returns when a token is passed, but this is minor given the tool's simplicity.

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 fully compensates by explaining that the token parameter is an optional JWT and that omitting it returns a login link. It even specifies the exact call shape `{ token: '<jwt>' }`, which is more than the bare schema provides.

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: authenticating to MCP.AI by logging in via browser and acquiring/using an access token. It provides specific actions ('log in in the browser, copy the access token') and distinguishes its role from siblings like 'connect' implicitly, though it doesn't explicitly name alternative tools.

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

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

The description gives concrete usage guidance for two scenarios: permanent connection via config header and session-only login via the token parameter or no-args link generation. It uses 'Best' and 'Or' to prioritize approaches, giving the agent clear context for when to use each call variant.

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 and idempotentHint, but the description adds behavioral context: the exact return states (authenticated:true, empty pending[], connect_url, per-install URLs). This goes beyond the structured 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?

Two concise sentences fully describe the tool's purpose and conditional behavior. No filler or repetitive content; every sentence 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?

The tool is simple, has no parameters, and no output schema, but the description covers both operational states and the key returned fields. This is complete for the tool's complexity and annotation support.

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 no parameter explanation is needed. The baseline of 4 applies because the description cannot add parameter meaning where none exist.

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', identifying the resource (connection status) and the action. It also distinguishes its behavior across states, which differentiates it from sibling tools like authenticate.

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 conditions for when different outputs appear ('When all providers are connected' vs 'When credentials are missing'), implying use for checking connection status. It does not explicitly name alternatives or state when not to use it, but context 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?

The description adds context about the read-only nature (consulta), the fact that data is not confidential (não é dado sigiloso), and the client's responsibility under LGPD. These go beyond the annotations, which only state readOnlyHint and idempotentHint. However, it does not disclose potential side effects or error conditions, so transparency is moderate.

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 relatively concise, consisting of three sentences without excessive verbosity. However, it includes redundant phrases about official sources and legal responsibilities, which could be streamlined. It is not poorly structured but could be more focused.

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 provides some context about the source and legal/payment aspects but omits any details about the expected output or return format. Since there is no output schema, the description should have clarified what the tool returns. It also lacks parameter explanations, making it incomplete for a user to effectively invoke the 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?

Schema coverage is 0% as the description does not explain any of the five parameters (login_cpf, login_senha, pkcs12_cert, pkcs12_pass, codigo_parcela). Given the requirement that descriptions must compensate for low schema coverage, this is a major gap, making the parameters semantically opaque.

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 a query for parcel details from INCRA SIGEF, an official Brazilian source. It specifies the resource (parcela) and the action (consulta), which is unambiguous. However, it does not explicitly use a verb like 'retrieve' or 'fetch', but 'consulta' is sufficient.

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 mentions payment (pague por consulta) and legal compliance (LGPD), but does not provide clear guidance on when to use this tool over alternatives or when not to use it. It lacks instructions on prerequisites or scenarios, so usage guidelines are weak.

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 important behavioral context beyond the annotations: it explains that invoke works even when the MCP is not installed and runs one-off without bloating the toolkit, it mentions connect/checkout flows return links rather than errors, and clarifies that write operations require workspace owner/admin. While the annotations are minimal (not read-only, not destructive), the description proactively discloses these nuances. It doesn't describe every action's side effects (e.g., uninstall behavior), but for a multi-action tool this is substantial. No contradiction with annotations, so no score penalty.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-organized, front-loading the overall purpose and then flowing from core discovery flow to nuanced execution semantics (invoke vs install), permissions, and finally the prompt library extension. Every sentence adds distinct value; there is no filler. However, it is long and may benefit from bullet points to ease scanning, but still earns a high score for its efficiency.

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 high complexity (14 actions, 23 params, no output schema), the description covers the main workflows, distinguishes invoke from install, mentions auth/payment edge cases, and outlines the prompt library side. It does not enumerate every action's exact response format or error handling, but it gives enough operational guidance to make the tool usable. A 5 would be reserved for something like per-action parameter substitution, but this is well above average.

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 23 parameters with 0% coverage (no parameter descriptions), but the overall description explains the core parameters (action with its enum values, mcp_id, tool_id, arguments, prompt-related params) by embedding them in the workflow explanation. It clarifies the meaning of action values like invoke, install, search_prompts, and mentions prompt variables. However, not every parameter is explicitly explained (e.g., immediate, tier_slug, conversation, prompt_targets), so it doesn't fully compensate for the missing schema coverage, but it does add meaningful semantics that the agent cannot infer from the bare JSON.

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

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

The description clearly states that marketplace is the official mcp.ai catalog and execution platform, explicitly listing all its capabilities (search, describe, invoke, install, etc.) and distinguishing it from a simple tool. It names the target resource (MCPs and prompts) and the actions performed, making it unmistakable even among sibling tools like authenticate or connect.

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

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

The description provides explicit guidance on when to use which action and how they relate: 'Core flow: action=search... → describe... → invoke RUNS that tool', contrasts invoke vs install ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), mentions auth/wallet edge cases ('invoke returns a connect link', 'returns a checkout/top-up link'), and tells users to use list_tools for currently callable tools and request_mcp when nothing fits. It also notes write operations require owner/admin. This exceeds expectations.

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 this is not read-only, not destructive, and idempotent. The description adds the useful behavioral note about including the conversation array for reproduction, but it does not disclose what happens after reporting (e.g., issue creation, response 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?

Two sentences, front-loaded with the core purpose, and every word contributes. No fluff or repetition of schema 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 simple reporting tool with annotations and a minimal schema, the description is largely complete. It lacks output details and side-effect disclosure, but the tool's simplicity and annotation coverage reduce the need for extensive 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?

Schema coverage is 0%, so the description carries the burden. It explains the conversation parameter's purpose, but message and context are not explicitly described beyond the general tool purpose. The description also calls conversation an 'array' while the schema types it as a string, which could cause minor confusion.

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 a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'), making the tool's purpose immediately clear. It also distinguishes this from sibling tools like authenticate 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 context for when to use the tool (bug, missing feature, feedback) and instructs the user to include the conversation array for reproduction. It does not explicitly mention alternatives or exclusions, but no close sibling tool exists.

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, covering the safety profile. The description adds slight context about what versions are shown (platform and adapter) but does not disclose additional behavioral traits such as network calls or output format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no wasted words. It states the action and the object clearly without 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?

For a no-parameter, read-only version-check tool, the description is fully adequate. It explains what the tool returns (platform and adapter versions) even without an output schema, and the annotations cover the operational safety 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 tool has zero parameters, so the baseline is 4. The description adds no parameter information, but none is needed since the schema is empty and there is nothing to clarify.

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 action ('Show') and specific resource ('current MCP platform and adapter versions'). It is distinct from most sibling tools, though it does not explicitly differentiate from the similarly named 'toolkit_info' sibling.

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?

No guidance is provided about when to use this tool versus alternatives such as 'toolkit_info' or other informational tools. The intended usage is implied by the name and description, but no explicit context or exclusions are given.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that it returns several types of state info, which is useful, but it doesn't disclose any additional side effects or behaviors beyond what annotations indicate. No contradiction.

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 lists all the key information points without any filler. It is front-loaded with the main action and clearly enumerates the return content.

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 zero parameters, no output schema, and the annotations cover safety, the description is complete enough. It specifies what state details are returned, which is sufficient for an agent to invoke it. No additional context seems necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema coverage is 100% (n/a). The description doesn't need to explain parameters, so a baseline of 4 is appropriate. It does explain what the output contains, which is the key semantic information.

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 the current toolkit state, listing specific resources: installed MCPs, connection status, connected accounts, and catalog tool counts. This verb+resource combination is specific and distinguishes it from siblings like 'show_version' and 'authenticate'.

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 inspecting the toolkit state, which is clear context. It does not explicitly state when not to use it or mention alternatives, but given the simplicity of the tool, the context is sufficient.

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