Tribunal TSE: Processo Judicial Eletrônico (PJe)

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

The description discloses behavioral traits beyond annotations: it explains the two login modes (permanent via config vs session-only via token) and what the no-args call returns (a link). It does not contradict annotations (idempotentHint=true, destructiveHint=false). It adds context about the auth flow, though it doesn't mention error handling or token validation outcomes.

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 somewhat long but well-structured with a lead sentence followed by 'Best:' and 'Or' alternatives. Each sentence contributes necessary information, and the most important purpose is front-loaded. No repetitive or irrelevant 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?

For a simple tool with one optional parameter and no output schema, the description covers the main actions: how to obtain a link, how to authenticate with a token, and the distinction between permanent and session-based access. It misses potential edge cases (e.g., invalid token behavior), but overall it's complete enough for an agent to invoke 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 coverage is 0%, so the description must compensate. It clearly explains the 'token' parameter as an optional JWT to paste for session login, and specifies that passing no args gets the link. This adds meaning beyond the bare schema definition, effectively documenting the parameter's role and optionality.

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, with specific instructions to log in via browser and obtain a token. It distinguishes itself from siblings like 'connect' by focusing on authentication, not general connectivity. The verb and resource are explicit, and it's not a tautology.

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 instructions: either add the token to server config for a permanent connection, or paste it for session-only login, and how to call with/without arguments. It gives context on when to use each mode, though it doesn't explicitly mention when to avoid this tool versus alternatives like 'connect'.

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 concrete behavioral detail beyond the annotations: authenticated:true with empty pending arrays, connect_url for the toolkit, and per-install URLs when credentials are missing. This is useful edge-behavior disclosure and does not contradict 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 compact and well-structured: one opening sentence states the primary purpose, and the second details the principal edge cases. Every sentence adds value with no filler 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?

Given the tool has zero parameters, no output schema, and rich safety annotations, the description covers the main success and missing-credential cases well. It could further explain partial connection states or the exact structure of pendingUrls, but this is sufficient for a simple no-parameter status 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 tool has no parameters, so schema coverage is effectively complete and no parameter documentation burden falls on the description. It appropriately does not try to explain non-existent inputs.

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's action and scope: it 'Returns connection status and URLs' and explains the two main outcomes. This distinguishes it from siblings like 'authenticate' by focusing on status inspection rather than performing an auth flow.

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 meaningful conditional context ('When all providers are connected...', 'When credentials are missing...'), which implies checking connection status before taking action. However, it never explicitly says when to use this tool instead of a sibling like 'authenticate', so usage guidance is only implied, 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?

The description goes well beyond the annotations by disclosing key behaviors: invoke runs tools even when not installed (one-off), returns connect or checkout links when credentials or payment are needed, and that writes require admin. It also explains the distinction between installed_in_toolkit vs installed_in_workspace and the prompt library's shareable links. No contradictions 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 lengthy (multiple paragraphs) but well-structured: first paragraph introduces the marketplace and core flow, second dives into the invoke behavior, third covers permissions, and fourth describes the prompt library. Information is front-loaded with the most critical details. While it could be tightened, every sentence adds value, so it earns a 4 rather than a lower score for wordiness.

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 (23 parameters, 14 actions, multiple sub-systems), the description is remarkably complete. It covers the end-to-end flow, edge cases (non-installed MCPs, credential/payment links), permissions, and the separate prompt library. Without an output schema, it explains enough about returns (e.g., connect/checkout links) to guide the agent. It fully equips an agent to decide when and how to use 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?

With 23 parameters and 0% schema description coverage, the description must compensate. It explains the action enum thoroughly (each action's purpose), and references key parameters like mcp_id, tool_id, arguments, and prompt_* in the flow explanations. Some parameters (e.g., limit, immediate, conversation) are not explicitly described, but the overall semantics for the primary use cases are covered. It doesn't fully enumerate every parameter but provides enough context to infer most.

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 the official mcp.ai marketplace catalog and execution platform, with specific actions (search, describe, invoke, install, etc.). It distinguishes itself from siblings by being the central hub for discovering and running MCPs, and it mentions the prompt library as an additional capability, making its purpose unmistakable.

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 each action: use invoke for one-off runs, install for permanent additions, search/describe for discovery, and prompt functions for prompt text. It also contrasts with alternatives (e.g., 'prefer invoke for a single/occasional use' versus install) and notes permission requirements (writes need workspace owner/admin), giving clear when-to-use and when-not-to-use context.

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 does not disclose side effects (e.g., whether it creates an issue, sends a notification, or modifies data). Annotations indicate it is not read-only, but the behavior beyond the description is unclear. This lack of transparency is a gap.

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 extremely concise, using one clear sentence to convey the purpose and a critical usage instruction. No unnecessary words 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 description covers the primary purpose and a key detail for reproduction (conversation array), but it omits explanations of the other parameters, potential side effects, and any output expectations. Since there is no output schema, the description is adequate for basic usage but leaves several aspects unspecified.

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 only mentions the 'conversation' parameter, instructing to include it, but does not explain its structure or the purpose of 'message' and 'context'. With zero schema description coverage, the description adds very little to clarify parameter meaning, leaving most parameters undocumented.

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.' This is a specific verb and resource that distinguishes it from sibling tools 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 tells when to use it (when reporting a bug or feedback) and includes a specific instruction to include the conversation array for reproduction. However, it does not explicitly mention alternatives or situations where it should not be used, so the guidance is solid but not as explicit as the 'search_calls' example.

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, so the description's job is light. It adds useful context by specifying exactly what is displayed (platform and adapter versions) without contradicting the read-only, non-destructive 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 a single, front-loaded sentence with no filler. Every word contributes meaning.

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, idempotent version-inspection tool, the description fully covers the tool's purpose with support from rich annotations. No output schema exists, but the description's statement of what is shown is sufficient for such a simple operation.

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 100% and no parameter explanation is needed. The baseline of 4 applies since there is nothing for the description to add beyond the already-complete 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 uses a specific verb ('show') and identifies the exact resource ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like authenticate or connect, which address different concerns.

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 wording implies the tool is for checking installed/runtime versions, but it gives no explicit when-to-use guidance or exclusions relative to sibling tools. There are no alternatives mentioned, yet the use case is straightforward enough that the implication may be 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context by specifying exactly what state is returned, which goes beyond the 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?

The description is a single, well-structured sentence that front-loads the main purpose and lists specifics without redundancy. Every phrase adds 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?

With no parameters and no output schema, the description carries the burden of explaining return values. It does so thoroughly by listing the four categories of returned state, making the tool's behavior fully understandable for an agent.

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 fully covers parameter semantics. The description appropriately focuses on the return content rather than parameters, earning the baseline 4 for no-parameter tools.

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 resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools 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 makes the tool's purpose clear, so an agent can infer it should be used to inspect toolkit state. However, it does not explicitly state when to prefer this tool over siblings such as show_version, nor does it provide exclusions or alternative tool 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?

The description adds context beyond the readOnlyHint annotation by mentioning prepaid credits, official source, and LGPD compliance (data controller responsibility). However, it does not discuss error handling, rate limits, or pagination, leaving some behavioral aspects opaque.

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 brief and to the point, but it repeats 'fonte oficial' and 'não é dado sigiloso' unnecessarily. Overall, it is concise enough and well-structured as a short paragraph.

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 lack of parameter explanations and no output schema, the description is incomplete. It does not specify how parameters combine, which are necessary, or what the response contains (e.g., case details, status). This leaves the tool under-specified for effective 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?

All 14 parameters are listed as optional strings with no descriptions in the schema, and the tool description does not explain any of them (e.g., 'uf', 'cpf', 'numero_processo'). With schema coverage at 0%, the description fails to compensate by providing parameter meaning or 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 it is a query tool ('consulta') for the TSE's Electronic Judicial Process (PJe) from an official source. It distinguishes itself from sibling tools like 'authenticate' or 'show_version' by its specific domain. However, it does not specify the exact type of query (e.g., searching by case number, party name) despite listing many parameters.

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 does not provide explicit guidance on when to use this tool versus alternatives. It mentions payment and official source but does not describe typical use cases or prerequisites. Since there are no similar sibling tools, this lack of explicit direction lowers the score.

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