Tribunal TJBA: Certidão do 1º Grau

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

The description discloses the main behavioral aspects: it can return a link when called without arguments, and it accepts a token for authentication. However, it does not mention potential errors (e.g., invalid token) or side effects beyond authentication, which would be transparent. Still, it provides more detail than typical 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 informative and well-structured, but slightly verbose. It could be condensed without losing key information. However, it is not excessively long and each sentence adds value, so it is still concise enough.

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 all necessary context for an agent: authentication methods, permanent vs. session options, and the no-args case. It does not require an output schema since the tool's behavior is fully described. It is complete for the intended use.

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 only parameter, 'token', is not described in the schema, but the description clarifies its purpose: it can be pasted for a session-only login or added to the server config for a permanent connection. This gives complete meaning to the parameter, fully compensating for the lack of schema description.

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: authentication for IDE agents. It provides specific instructions on how to authenticate, distinguishing it from sibling tools like connect 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?

It explicitly explains when to use the tool (for authentication) and gives three clear usage scenarios: adding token to config for permanent connection, pasting token for session, or calling with no args to get the link. This is more than sufficient for an agent to decide when and how to invoke 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 declare readOnlyHint:true and idempotentHint:true. The description goes beyond that by specifying the conditional response structure (authenticated:true with empty pending[], and connect_url when credentials are missing), adding behavioral context that is not present in the structured fields. No contradictions exist.

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, front-loads the core purpose ('Returns connection status and URLs'), and then adds conditional detail efficiently. Every word earns its place with no redundancy or filler.

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 all realistic states (all connected vs missing credentials) and identifies key return fields (authenticated, pending, connect_url, per-install URLs). No output schema exists, so the description carries the responsibility, and it does so adequately for 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?

The tool has zero parameters, and the schema confirms no parameters are needed. According to the rubric, 0 params defaults to a baseline of 4. The description rightly omits parameter details, and the schema covers the lack of inputs completely.

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' with a clear resource ('connection status and URLs') and explains two output conditions (all providers connected vs missing credentials), effectively distinguishing it from sibling tools like authenticate or 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 provides clear context on when different outputs appear (when providers are connected vs when credentials are missing), implying appropriate use cases. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.

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 sparse annotations, the description discloses that invoke runs tools even when not installed, returns connect/checkout links for auth/payment issues, and that writes require workspace owner/admin. It also explains installed_in_toolkit vs installed_in_workspace flags, adding valuable operational context.

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, packing a lot of necessary information but lacking visual structure. It is not concise; breaking it into bullet points or separating the prompt library would improve readability without losing 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's complexity (14 actions, 23 parameters, no output schema), the description covers most major behaviors including auth, billing, install-vs-invoke semantics, and the prompt library. However, it omits actions like 'resume' and several parameters, so it is not 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?

With 0% schema description coverage, the description compensates by explaining the roles of action, tool_id, mcp_id, arguments, and prompt_* fields within the workflows. However, it does not cover all 23 parameters (e.g., limit, immediate, resume, cancel_reason), leaving some gaps for the agent.

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 is the official mcp.ai marketplace, serving as both a catalog and execution layer for MCPs/tools. It specifies core actions (search, describe, invoke, install) and effectively distinguishes itself from narrower sibling tools by covering the full lifecycle.

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 usage guidance, e.g., 'prefer invoke for a single/occasional use' and 'use install only to make an MCP PERMANENT'. It also explains when to use request_mcp ('when nothing fits') and what list_tools is for, offering strong alternatives within 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 specify readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds the important behavioral requirement to include the conversation array for reproduction, which helps the agent understand necessary inputs. It does not contradict any annotation and provides useful context beyond the structured metadata.

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, with the primary purpose stated first and a vital usage instruction second. There is no fluff or redundancy; every word provides useful information.

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 tool with three parameters and no output schema, the description covers the core purpose and one parameter but omits an explanation of the 'context' parameter and does not describe the expected response or side effects. This leaves minor but noticeable gaps in completeness.

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 for all parameters. It explains the purpose of the conversation parameter ('recent messages for reproduction') but does not explicitly define the required 'message' parameter or the optional 'context' parameter. This leaves significant gaps in parameter understanding.

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.' The verb 'Report' and specific resources (bug, missing feature, feedback) make it unambiguous. It also distinguishes from siblings like authenticate and marketplace, which serve entirely different functions.

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 the tool: to report issues or feedback. It does not explicitly list alternatives or exclusions, but the sibling tools are so different that confusion is unlikely. This is a minor omission, hence a 4 rather than a 5.

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 'Show...' aligns with these. The description adds no additional behavioral context beyond the annotations, but none is strongly needed for a read-only version query.

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 directly to understanding the tool's purpose.

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 version query with strong annotations, the description provides sufficient context. The output is not formally specified, but the description clearly states what information is shown (MCP platform and adapter 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 tool has zero parameters, and the schema coverage is 100%, so no parameter explanation is needed. The baseline of 4 applies because there are no parameters for the description 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 uses a specific verb ('Show') and resource ('current MCP platform and adapter versions'), making the tool's function immediately clear. It also differentiates from siblings like toolkit_info by focusing specifically on version information.

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 should be used whenever version information is needed, but it does not explicitly discuss when not to use it or mention any alternatives. For a simple zero-parameter query, this minimal usage guidance is acceptable but not fully explicit.

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, which the description does not contradict. The description adds valuable context beyond annotations by detailing exactly what state will be returned (installed MCPs, connection status, accounts, counts), which helps an agent anticipate the tool's output without needing further calls.

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, well-structured sentence that front-loads the core purpose and then lists specific return elements. Every phrase earns its place, with no redundancy or unnecessary words. It is concise yet comprehensive.

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 (no parameters, no output schema, no nested objects), the description covers all essential aspects of what the tool does and what it returns. It could optionally mention whether the information is real-time or cached, but this is not critical for basic usage. The description is fully sufficient for an agent to decide to call it.

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 trivially 100%. Per the rubric, the baseline for 0 parameters is 4, and since there are no parameters to describe, the description does not need to compensate. No parameter semantics are relevant here.

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 what the tool does with a specific verb ('Returns') and a precise resource ('current toolkit state'). It enumerates the exact pieces of information provided (installed MCPs, connection status, connected accounts, catalog tool counts), which differentiates it from sibling tools like 'connect' or 'authenticate' that involve state changes.

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 a use case: to inspect the toolkit state. However, it does not explicitly state when to prefer this over alternatives or mention any exclusions (e.g., 'use this before authentication' or 'for connection issues, use connect'). The usage context is implied but not explicitly guided.

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 (readOnly, idempotent, non-destructive), the description adds meaningful behavioral context: no credentials are required, there is a prepaid credit cost model, the data is not confidential, and the caller is the LGPD data controller. This materially helps the agent understand side effects and obligations.

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 key purpose in the first sentence, and each subsequent sentence adds meaningful operational or legal context. No redundant filler is present, and the length is appropriate for the amount of information conveyed.

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 12 unrequired, undocumented string parameters and no output schema, the description is not complete enough for correct invocation. It explains the source and legal context, but does not specify which identifiers or filters are necessary, how to combine them, or what kind of certificate query inputs are accepted. The agent would need external knowledge to use this tool correctly.

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% across 12 parameters, and the description does not mention any parameter semantics, required combinations, or identifier selection guidance (e.g., when to use CPF versus CNPJ versus nome). The description adds no value beyond the raw property names in the schema, so the agent gets almost no help with parameter usage.

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 verb+resource: consulta/certidão do 1º Grau no Tribunal TJBA em fonte oficial. This distinguishes the tool from the generic sibling tools (authenticate, marketplace, etc.) and makes the main purpose immediately obvious.

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 usage context: hosted by the platform, no platform credentials needed, requires prepaid credit per query, and queries official Brazilian citizen-available data. It does not explicitly list exclusions or alternatives, but the context is strong enough for an agent to understand when this tool is appropriate.

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