Registradores (ARISP) Matrícula: Download de Matrícula

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

It discloses important behavioral context beyond annotations: the difference between permanent config-based auth and session-only token auth, plus the two invocation modes. It does not detail possible side effects or error behavior, but annotations already mark it non-destructive and idempotent.

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 technically informative, with no truly wasted content. However, it is written as one long run-on paragraph and mixes audience context with usage instructions, so it is not optimally structured or 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?

Given one optional parameter, no output schema, and only sparse annotations, the description covers the essential workflows: no-args returns a link, token enables session login, and config header enables permanent auth. It does not state the exact response format or failure modes, but it is largely complete for an authentication 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 schema only provides a bare 'token' string with no description, and schema coverage is 0%. The description compensates by explaining the token is a JWT, is used for session-only login, and that omitting it returns the login link, giving the agent enough semantic information to invoke the tool correctly.

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 handling authentication to MCP.AI for IDE agents, explaining both token-based login and link retrieval. It is more than a restatement of the name, but it does not explicitly differentiate itself from sibling tools like '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 gives concrete when-to-use guidance: add the token to server config for a permanent connection, or pass it as a session-only login, or call with no args to receive the login link. It lacks an explicit exclusion of when not to use this tool versus 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 declare it as read-only (readOnlyHint: true) and idempotent. The description adds valuable behavioral context beyond that: it explains the exact fields returned (authenticated, pending, connect_url, per-install URLs) and the conditions under which they appear. This enriches the agent's understanding of the tool's behavior without contradicting any 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 only two sentences long, immediately front-loads the main purpose ('Returns connection status and URLs'), and uses every word. It is concise, well-structured, and free of redundancy. This is a model of 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?

Despite having no output schema, the description fully explains the return value structure and conditional behavior. It covers both the success case (authenticated:true) and the failure/missing-credentials case (connect_url and per-install URLs). For a zero-parameter read-only tool, this is a complete and sufficient description.

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 0 parameters and 100% schema coverage, so the baseline is 4. The description does not need to explain parameters that don't exist, and it adds no irrelevant details. It correctly describes the tool's behavior without parameter documentation 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 uses the specific verb 'Returns' and clearly identifies the resource: connection status and URLs. It distinguishes itself from siblings like 'authenticate' by focusing on status retrieval, and it explains conditional behavior (what happens when providers are connected vs missing credentials), which is specific and unambiguous.

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 this tool (to check connection status) and provides useful context about the response in different states. It doesn't explicitly state alternatives or exclusions, but for a read-only status tool, the usage context is quite clear and self-sufficient. The absence of an explicit 'when not to use' is acceptable given the tool's simplicity.

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?

Beyond annotations, it discloses one-off execution without installation, connect/checkout link behavior, workspace owner/admin requirement for writes, installed_in_toolkit vs installed_in_workspace flags, and the no-login share link. No contradiction with annotations; readOnlyHint=false is consistent with writes.

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 front-loaded with the core flow, and every sentence adds operational detail. It is long, but justified by 23 parameters and 14 actions; minor structural improvements (bullets/sections) would help.

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 complex multi-action tool with no output schema, it covers the main flows, auth, billing, and prompt library well. Gaps remain around exact return shapes and several action-specific parameters, but the agent can select and invoke correctly 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 coverage, the description compensates by explaining the action enum and key parameters (mcp_id, tool_id, prompt_slug, prompt_vars implicitly). However, many parameters (arguments, immediate, tier_slug, cancel_reason, conversation, request_details, etc.) remain undocumented, so it doesn't fully carry the burden.

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 marketplace as the official mcp.ai catalog and execution layer, with a concrete core flow (search → describe → invoke) and a second prompt-library capability. It distinguishes itself from siblings by naming report_bug and by contrasting invoke vs install vs list_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 guidance: prefer invoke for one-off use, use install only for permanent toolkit membership, list_tools for currently callable tools, request_mcp when nothing fits, and search_prompts/get_prompt/publish_prompt for prompt text. This is strong when/when-not guidance with named 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?

Beyond the readOnlyHint/idempotentHint annotations, the description discloses that each query costs money ('pague por consulta com crédito pré-pago'), that no platform credentials are needed, and includes LGPD data responsibility details. This adds significant behavioral context beyond annotations, though it could elaborate on the request lifecycle or error handling.

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 and then covering payment, data source, and legal caveats. It is not bloated, though the legal disclaimer could be considered a separate note. Overall, 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?

The description covers cost, credential handling, and data sensitivity, which are useful for a complex tool with 6 parameters and no output schema. However, it does not mention the return format, how parameters relate (e.g., email/senha vs pkcs12_cert), or any specific usage examples, leaving the agent to guess on invocation details.

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 no explanation of the six parameters (email, senha, tipo_login, pkcs12_cert, pkcs12_pass, numero_pedido), the description fails to guide the agent on how to populate them. The phrase 'sem credenciais da plataforma' hints that credentials are for an external system, but this is minimal and does not compensate for the lack of explicit parameter documentation.

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 it is for downloading/querying 'Matrícula' from official sources, specifically mentioning ARISP, which is a specific verb+resource. It differentiates from the generic sibling tools like 'authenticate' and 'connect', though the relationship between 'download' and 'consulta' could be crisper.

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 provides context that this is a paid service using prepaid credit and does not require platform credentials, which helps set expectations. However, it lacks explicit when-to-use versus alternatives or exclusions, and does not reference sibling tools like 'authenticate' or 'connect' that might be confused with it.

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 provide readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds the important behavior that recent messages should be included as a conversation array for reproduction. However, it does not clarify what the user can expect after submitting, such as confirmation or how the data is handled.

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 short sentences and front-loads the purpose. Every sentence adds value and there is 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?

For a small bug-reporting tool with one required parameter and no output schema, the description is adequate. It gives purpose and the key reproduction guidance, though describing the format of 'conversation' and the purpose of 'context' would make it fully complete.

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 carry parameter meaning, but it only describes the 'conversation' parameter as containing recent messages. It does not explain the required 'message' parameter or the 'context' parameter, leaving the most important input unclear.

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 'Report' and the resources involved: bug, missing feature, or feedback. It is readily distinguished from sibling tools like authenticate, connect, show_version, and 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 provides clear context for when to use this tool, covering bug reports, missing features, and general feedback. It does not explicitly list when not to use it or name exact alternatives, but no sibling tool competes for the same purpose.

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, and the description's 'Show' verb aligns perfectly. The description adds useful scope—that it reports both platform and adapter versions—without omitting any relevant 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 a single, front-loaded sentence with no filler. Every word contributes to conveying the tool's purpose and scope.

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 informational tool with full annotation coverage, the description fully covers what the agent needs to know. No output schema exists, but 'show versions' implies the return format well enough for typical agent decisions.

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 schema description coverage is trivially 100%. The description appropriately omits parameter details since none exist, and the baseline score of 4 applies.

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 the specific verb 'Show' with a clear resource ('current MCP platform and adapter versions'), making the tool's function immediately obvious. This distinguishes it from sibling tools like connect, authenticate, or report_bug, none of which relate to 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?

No explicit when-to-use guidance or alternatives are provided, but the tool's purpose is self-evident as a version-check utility. The usage context is implied (invoke when needing version info), which is adequate for such a simple, standalone 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=true and destructiveHint=false, so the safety profile is established. The description adds value by detailing what the state includes (installed MCPs, connection status, accounts, tool counts), providing actionable transparency about the return content beyond the mere 'safe operation' implication.

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 delivers all necessary information without redundancy. It is front-loaded with the action ('Returns') and specifies exactly what is returned, making every word earn 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?

For a zero-parameter, read-only info tool with no output schema, the description is fully self-contained. It enumerates all the categories of data returned (MCPs, statuses, accounts, catalog counts), leaving no ambiguity about the tool's scope or return content.

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, and the schema coverage is 100% (vacuously complete). The description correctly focuses on the return value rather than parameters. With no parameters to clarify, the baseline of 4 is appropriate as the description doesn't need to compensate for missing schema 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 names the exact resource ('current toolkit state') and its composition (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like 'show_version' 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 clearly implies the tool is for retrieving a snapshot of the toolkit's current configuration and status, which is a common read-only need. While it doesn't name alternatives explicitly or state exclusions, the context (read-only state vs. sibling actions) makes appropriate usage evident.

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