Tribunal TJSP: Lista de Processos (eproc)

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

The description reveals key behaviors: it may open a browser, accept a pasted JWT, and support both persistent and session-based login. It adds context beyond the annotations, such as the config header recommendation for a 'permanent, non-expiring connection,' while not contradicting the read-only or idempotent hints.

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 run-on sentence that mixes instructions, recommendations, and invocation examples, making it harder to parse. Although it contains all necessary information, better formatting (e.g., bullet points or separate sentences) would improve clarity.

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 auth tool with one optional parameter and no output schema, the description covers the essential flow: obtaining a link, pasting a token, and the two authentication modes. It could mention what happens after successful login (e.g., token storage), but it is complete enough for typical usage.

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 the 'token' parameter: call with { token: "<jwt>" } for session login, or with no args to retrieve the login link. This gives complete semantic clarity for the only parameter.

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 this tool authenticates users via browser login and handles access tokens, with a specific verb ('log in') and resource (IDE agent access). It differentiates from siblings by naming the product context ('MCP.AI for IDE agents') and the unique auth flow, which distinguishes it from 'connect' and other 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 explains when to use the tool with different arguments: no args to get a login link, or with a token for session login. It also contrasts permanent (config header) vs session-only methods, giving clear usage context even though it does not name sibling tools explicitly.

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 read-only, idempotent, and non-destructive behavior, so the description adds value by disclosing conditional outputs: authenticated:true with empty pending[] versus connect_url and per-install URLs. This 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?

Two sentences, front-loaded with the core purpose, followed by concise conditional behavior. Every sentence adds useful information 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?

The description is complete enough for a zero-parameter status tool with strong annotations. It covers the two main scenarios and key return fields (authenticated, pending, connect_url), though a bit more detail about the structure of per-install URLs could make it fully comprehensive.

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 there is nothing for the description to explain about parameters. The baseline of 4 is appropriate given no parameters 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, using a specific verb ('Returns') and resource ('connection status'). It also distinguishes itself from sibling tools like 'authenticate' by indicating it is a read-only status check rather than an authentication action.

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 contextual guidance by explaining what happens when all providers are connected versus when credentials are missing. It does not explicitly mention alternatives or exclusions, but the conditional behavior effectively tells an agent when to use this tool for status checking.

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 are minimal (readOnlyHint false, openWorldHint true), so the description carries the burden. It discloses that invoke runs tools without installation and can return connect/checkout links, which is critical behavioral context. It also mentions permission requirements for writes (requires workspace owner/admin) and flags installed status flags. No contradiction with annotations. Slight deduction for not detailing what happens on uninstall/cancel or error behavior beyond the common cases.

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 long single paragraph with dense information, mixing multiple concepts (core flow, invoke nuances, install guidance, prompt library). It front-loads the main purpose but then lists many details without clear structure, making it hard to scan. Could benefit from bullet points or distinction between marketplace and prompt library. Still, it covers necessary content, so it is not overlong for the complexity but poorly structured.

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 params, no output schema), the description is quite comprehensive: it covers the search-to-invoke flow, installed vs invoke behavior, auth and payment links, permissions, and the prompt library. It doesn't explain every return value or parameter, but it provides enough for an agent to use the tool effectively for most use cases. Without an output schema, the description could be more explicit about what each action returns, but it does state the purpose of each action.

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 23 parameters. It explains the semantics of key parameters implicitly (action, query, mcp_id, tool_id, arguments) by describing the flow, and mentions specific sub-actions and their parameters (e.g., prompt_title, prompt_vars). However, many parameters are not explained (limit, immediate, tier_slug, conversation, etc.) and their meaning must be inferred from the action. The description adds some value but leaves gaps for a complex tool.

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' and enumerates its multiple capabilities (search, describe, invoke, install, prompt library). It distinguishes the main flow and mentions key actions like invoke and install. However, it is a broad multi-purpose tool, and the description is dense, making it partially unclear which specific action the agent should use for a given query. It does differentiate from siblings by naming specific sub-actions and contrasting with other 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?

Provides explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use'), when to use search vs describe (core flow), and mentions that list_tools lists callable items. It also covers subscription handling and error paths (connect link, checkout link). Clearly indicates when to use alternatives like request_mcp. This is thorough and directly guides selection among the many actions.

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 idempotentHint=true and destructiveHint=false, covering the safety profile. The description adds behavioral context beyond annotations by explaining the need to include the conversation array for reproduction, which guides the agent on how to make the report useful.

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 compact sentence plus a short directive, conveying all essential information without fluff. Every word contributes to understanding the tool's purpose and usage.

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 low complexity (3 simple params, no output schema), the description adequately covers the purpose, required input behavior, and a key parameter. It omits return behavior, but that is not critical for this type of reporting tool, and annotations fill in safety semantics.

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. It does explain the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'), but it gives no guidance on 'message' (required) or 'context' beyond what the schema names imply. This partial compensation earns a mid-range score.

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.' This gives a specific verb (report) and resource (bug/feature/feedback), distinguishing it from sibling tools like authenticate or marketplace, which serve entirely different purposes.

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 instruction: 'Include the conversation array with recent messages for reproduction.' This tells the agent a critical prerequisite for effective use. While it doesn't explicitly state when not to use this tool, the sibling set is clearly unrelated, so the context is unambiguous.

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 convey read-only and idempotent behavior. The description adds minor context by specifying 'current' versions, implying a live fetch, but it does not disclose additional behavioral traits beyond the annotations. Given the lower bar with annotations present, this is adequate.

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 with no redundancy. It is well-structured and directly states the tool's purpose without extraneous words.

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 (no parameters, no output schema), the description sufficiently explains what it does. It implies the return of version information but does not explicitly describe the output format. However, for a display tool, this is adequate.

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 baseline is 4. The description does not need to explain parameters since none exist, and it does not add conflicting 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's function: showing the current MCP platform and adapter versions. The verb 'show' and the specific resource (versions) make the purpose unambiguous, and it is easily distinguishable from 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 implies usage (when you need to know versions) but does not explicitly state when to use this tool versus alternatives. It provides no exclusion criteria or comparison to other tools, which falls under 'implied 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 indicate readOnlyHint, idempotentHint, destructiveHint false. The description enhances this by specifying exactly what state is returned (installed MCPs, connection status, accounts, catalog tool counts), adding value beyond the annotations. 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, well-structured sentence that front-loads the action ('Returns the current toolkit state') and then elaborates with specific details. Every part 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?

With no parameters and no output schema, the description exactly specifies what is returned (installed MCPs, connection status, accounts, catalog tool counts). This is sufficient for an agent to know what to expect, making the tool's behavior fully described.

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?

No parameters exist, so the description doesn't need to explain them. Baseline for zero-param tools is 4 per rubric, and the description aligns with the empty schema. It clearly conveys what the tool returns without needing parameter context.

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, specifying exactly what it includes (installed MCPs, connection statuses, accounts, and catalog tool counts). This verb+resource construction distinguishes it from sibling tools like authenticate/connect, which are action-oriented.

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 check toolkit status), but does not explicitly state when not to use it or point to alternatives. Given the sibling names (authenticate, connect, etc.), the use case is obvious, so it earns a 4.

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 communicate read-only, idempotent, non-destructive behavior. The description adds useful behavioral context beyond that: no platform credentials are required, each query consumes prepaid credit, the data is official and non-confidential, and LGPD obligations apply. This meaningfully supplements 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 reasonably concise and front-loaded with the core purpose, followed by relevant operational and legal context. Although the LGPD sentence adds some boilerplate, the overall structure is clear and not wasteful.

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 has four optional parameters and no output schema, yet the description does not explain parameter selection, return format, or pagination behavior. It covers billing and legal aspects but leaves essential usage details undocumented.

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% and the description does not mention cpf, oab, cnpj, or nome_parte at all. With four undocumented optional parameters, the description fails to compensate or clarify which identifier to provide or how they interact.

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: consulting/listing TJSP court cases in the eproc system from an official source. The verb 'consultar' and resource 'Lista de Processos (eproc)' make the purpose specific, and it is easily distinguished from unrelated 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 implies usage context—querying official Brazilian court case information, without platform credentials and with prepaid credits—but it does not explicitly state when to prefer this tool over alternatives or exclude scenarios. It gives operational prerequisites but no direct 'use when' guidance.

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