Tribunal TJRJ: Visualizar Certidão

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

Annotations already indicate this is not read-only but is idempotent and non-destructive. The description adds useful behavioral context: a permanent config-header path versus a session-only token path, plus the fact that no args produces a login link. It does not detail all possible response formats or side effects, but the added context is meaningful.

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 compact and every part earns its place: it states the target audience, explains the permanent configuration approach, and gives a clear no-args vs token invocation. It uses concrete examples without excessive wording.

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 optional-parameter authentication tool without an output schema, the description covers the input behavior and setup path well. It does not describe the exact shape of the returned link/response, but it conveys enough for an agent to guide the user through the login flow.

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?

Even though schema description coverage is 0%, the description explains the optional token parameter: it should be a JWT, it enables session-only login, and omitting it returns the login link. This compensates well for the minimal 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 states the tool's purpose: authenticating to MCP.AI for IDE agents via browser login or token. It specifies concrete actions (log in, copy token, call with token or no args), but it does not distinguish itself from sibling tools such as '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 explicit usage modes: add a bearer token to server config for permanent login, pass a token for session-only login, or call with no args to get the login link. It lacks explicit when-to-use vs. alternative tools, but the workflow guidance is strong 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?

The annotations already mark it as read-only and idempotent, and the description adds concrete behavioral details on output scenarios. This goes beyond what annotations alone convey, making side effects and outcomes 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 succinct, using two sentences to convey the core functionality and key conditional outputs. It avoids any unnecessary detail or 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?

The description covers the two main scenarios (all connected and credentials missing) but may omit edge cases like partial connectivity. Still, it sufficiently addresses the tool's primary purpose without an 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?

There are no parameters in the schema, so the description has nothing to explain. The absence of parameters is implicitly clear, and no further elaboration is 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 clearly states the tool returns connection status and URLs, specifying the conditions for authenticated vs. connect_url. It is distinct from sibling tools like authenticate or report_bug by focusing on status checking.

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 explains when the tool returns authenticated:true or connect_url, providing clear usage context. However, it does not explicitly contrast with alternatives or state when to prefer this over others, though the intent is 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?

Beyond annotations, it discloses that invoke works even for uninstalled MCPs without bloat, that credential/payment issues yield connect/checkout links, and that writes need owner/admin rights. No contradiction with annotations (readOnlyHint=false is consistent with these 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 long but well-structured, starting with the core purpose and flowing through the main workflow, key edge cases, permissions, and separate prompt library. It is front-loaded and mostly free of redundancy, though the final prompt-library section could be tighter.

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 14 actions and 23 parameters, the description covers the most important flows (search/describe/invoke/install), permission requirements, and return behaviors for describe, invoke, and publish_prompt. It does not fully specify return formats for every action (e.g., search, list_tools, subscribe), and there is no output schema to fill that gap, so it falls just short of a 5.

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 key parameters: action values (search, describe, invoke, install, list_tools, search_prompts, get_prompt, publish_prompt), tool_id, arguments, prompt_vars, prompt_slug, and prompt_body. However, some parameters like limit, immediate, tier_slug, conversation, and cancel_reason are not explicitly addressed, so it is not fully exhaustive.

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 a clear statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then details a core flow (search → describe → invoke) that defines the resource and its primary actions, distinguishing it from siblings like authenticate or connect by focusing on catalog/discovery/execution.

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?

Provides explicit usage guidance: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' Also explains when invoke returns connect/checkout links and to retry after the user acts, and notes that writes require workspace owner/admin. This gives clear when-to and when-not-to use each action.

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=false, idempotentHint=true, destructiveHint=false. The description adds little beyond 'report' and 'send feedback,' not detailing side effects or what happens after submission. It provides minimal additional context beyond 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 two concise sentences, directly stating the purpose and a key usage hint. It is well-structured and free of unnecessary detail.

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?

There is no output schema, and the description does not mention return values, error cases, or side effects. The tool's behavior beyond the basic act of reporting is unclear, making the description incomplete for fully understanding the tool's 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 schema includes parameter names, types, defaults, and required status, but the description only explains 'conversation' (for reproduction). The 'context' and 'message' parameters are not described, leaving their purposes ambiguous.

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 function: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('Report') and resource ('bug'/'feedback'), and is distinct from sibling tools (e.g., show_version, 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 gives a specific usage instruction: 'Include the conversation array with recent messages for reproduction.' While it doesn't explicitly say when not to use this tool versus alternatives, the purpose is clear enough to infer appropriate usage.

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 destructiveHint, so the safety profile is covered. The description adds that it reports 'MCP platform and adapter versions' but does not disclose whether it requires a connection or what exact output format to expect. This is minimal but not contradictory.

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 with no extraneous words. It is perfectly front-loaded and concise.

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, read-only tool with annotations covering safety, the description is adequate. It clearly states the main purpose, though it could mention whether it returns a simple string or structured data. The absence of an output schema means some ambiguity remains, but this is minor.

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 there is nothing for the description to explain beyond what the schema shows (which is already 100% coverage). Per the rubric, a zero-parameter tool earns a baseline of 4, and no additional semantic info is necessary.

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 identifies the exact resource ('current MCP platform and adapter versions'), making the tool's function unmistakable and clearly distinct from siblings like authenticate or report_bug.

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 on when to use this tool versus alternatives. It could mention scenarios like troubleshooting version compatibility or environment verification, but the description is purely descriptive with no contextual advice.

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 description does not need to repeat safety traits. It adds value by describing what information is returned (installed MCPs, connection status, accounts, catalog counts), which is useful context beyond 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, clear sentence that front-loads the purpose and lists specifics without any filler. Every element 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?

For a read-only state tool with no parameters and no output schema, the description sufficiently enumerates the key aspects of the state (installed MCPs, connection status, accounts, catalog counts). It could potentially mention the response format or whether the tool requires prior authentication, but annotations indicate it is read-only and safe, and the description covers the essential information.

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 per the rubric the baseline is 4. There is nothing to add about parameters; the description appropriately focuses on the return content.

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 details (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate or connect, which are operations rather than state queries.

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's current state, and sibling tools are clearly different operations. However, it does not explicitly state when not to use it or mention alternatives, so it lacks explicit when/when-not 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?

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses that using the tool incurs a cost ('pague por consulta') and includes a data responsibility disclaimer regarding LGPD. These are behavioral aspects not covered by annotations, enhancing transparency.

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 conveys necessary details (purpose, cost, data source, legal responsibility) without excessive verbosity. It is well-structured and appropriately sized for the information provided.

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 simplicity of the tool (one parameter, no output schema), the description covers purpose, cost, and legal context. However, it omits any details about the parameter or what the certificate result looks like, leaving some operational aspects incomplete.

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 description does not elaborate on the parameter 'numero_requerimento' (request number) at all. The schema provides no description for it, and the tool description adds no semantic meaning, leaving the parameter's purpose only inferable from its name.

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 as 'Visualizar Certidão, consulta em fonte oficial' (View Certificate, consultation in official source). It specifies the court (TJRJ) and the action (viewing a certificate), making the intent 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 mentions usage context: 'sem credenciais da plataforma, pague por consulta com crédito pré-pago' (no platform credentials, pay per consultation with prepaid credits) and clarifies that it accesses public, non-confidential data (não é dado sigiloso). However, it does not explicitly compare to alternative tools or state when to use this over others, limiting guidance.

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