Tribunal TRT5: Consulta Processual

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

Beyond the annotations (idempotent, non-destructive, not read-only), the description discloses key behaviors: calling with no args returns a link, passing a token establishes a session-only login, and configuring the header gives a permanent non-expiring connection. It explains the difference between session and permanent authentication, adding useful context on how the tool behaves.

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 slightly verbose but well-structured, with each sentence contributing necessary information. It front-loads the context (MCP.AI for IDE agents) and then guides through configuration options. It could be tightened but is efficient and not redundant.

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 all usage modes: permanent configuration via header, session login via token, and retrieval of the login link. It is complete enough for an agent to invoke correctly in various scenarios.

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 defines token as a string with no description. The description fully compensates by explaining that token is a JWT obtained from the browser, it is optional (can call with no args to get a link), and it is used for session-only login. This adds rich meaning beyond the raw 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 MCP.AI for IDE agents by logging in via browser and retrieving an access token. The verb "authenticate" is specific to the login action and is distinguished from siblings like "connect" by focusing on token-based authentication. The resource (MCP.AI access token) is explicitly mentioned.

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 scenarios: for a permanent connection, add the token as an Authorization header in config; for a session-only login, call with the token; for getting the login link, call with no args. It implicitly contrasts the permanent vs. session approaches but does not explicitly reference sibling tools like "connect" as alternatives. This is clear context without explicit exclusions.

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, covering the safety profile. The description adds valuable context beyond that by detailing the conditional return states (authenticated:true with empty pending[] vs connect_url and per-install URLs when credentials are missing). No contradiction with annotations; the description complements them with scenario-specific output 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 two tight sentences, front-loaded with the core purpose ('Returns connection status and URLs') followed by the two conditional states. Every sentence adds distinct value with zero filler words or redundant phrasing.

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 parameterless status tool, the description covers the main behavioral branches well. It could go slightly further by specifying the full response shape (e.g., what fields constitute the connection status, the structure of pending[]), but it places the key details about what happens in each state. Given no output schema exists, the description carries the return-format burden adequately.

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 description coverage is trivially 100% (empty properties object). With no params to document, the baseline is 4. The description instead focuses on output behavior, which is appropriate given the parameterless interface.

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+resource ('Returns connection status and URLs') and distinguishes the tool's behavior across two states (all providers connected vs missing credentials). It differentiates well from siblings like authenticate and toolkit_info, making the tool's role as a status/health reporter 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 this is a read-only status check to run when you need connection state or URLs, but it never explicitly states when to use this versus authenticate or other siblings. The two-state behavior (connected vs missing credentials) gives contextual hints about what to expect, but no direct guidance on alternatives or exclusions.

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 discloses many important behavioral details beyond the annotations: invoke runs a tool even when the MCP is NOT installed (one-off, without bloating the tool list), invoke returns a connect link when credentials are needed, invoke returns a checkout/top-up link if paid wallet is empty, the one-off install behind invoke requires owner/admin, search/describe flag installed_in_toolkit vs installed_in_workspace, and the separate prompt library (search_prompts/get_prompt/publish_prompt with shareable login-free links). It does not heavily disclose destructive/write risks, but the annotations (openWorldHint=true, destructiveHint=false) already cover some of the trust profile. Minor gap: it could explicitly state the mutating effects of install/uninstall on the toolkit beyond 'permanent', but the existing detail is strong. Note: readOnlyHint is false, so the description's mention of install/uninstall/subscribe as writes is consistent with 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 text is dense and substantial (almost half a page), but most sentences carry unique information about the tool's actions and flows. It is loosely structured in a single paragraph; breaking it into sections (Core flow / invoke behavior / install behavior / billing & admin / prompt library) would improve scanability. The information density is high and not bloated, but the lack of structure reduces readability for an agent doing quick decision-making.

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 25 parameters, no output schema, and many sub-actions (search/describe/install/invoke/subscribe/prompt-library), the description provides an unusually thorough map: the search→describe→invoke flow, the not-installed behavior, the auth/payment edge cases, the admin-required write actions, and the distinction between the MCP catalog and the prompt library. This nearly compensates for the lack of output schema and the 0% parameter schema coverage. It leaves some minor gaps (e.g., exact output/bucket_details per action, list_tools outcome), but for such a complex tool, it is very strong.

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% in the schema, but the description compensates with rich context about the core parameters: action (enum), mcp_id, tool_id, arguments (JSON string), and the prompt parameters (prompt_slug, prompt_body, prompt_vars, etc.). It explains what each major action expects (search uses query, invoke uses tool_id+arguments), and describes the response-driven flows (connect link, checkout link) that inform how arguments should be constructed. It does not explain every one of the 23 parameters (e.g., cancel_reason/cancel_comment, report_context, request_details are not individually described), but the overall coverage is much higher than 0%. Given 23 parameters and 0% schema coverage, the description is doing a substantial job.

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 provides a rich, specific explanation of what the marketplace tool does: it's the in-platform catalog of MCPs/tools and the way to run them. It clearly lists the core flow (search → describe → invoke) and enumerates each action verb with its distinct purpose (install, subscribe, list_tools, etc.), which distinguishes it well from sibling tools. It even mentions capability requests like "find an MCP that does X" and "consulta um CPF", giving a concrete sense of scope.

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 guidance on when to use each action: use invoke for single/occasional use (even when the MCP is not installed), use install only to make an MCP permanent, use list_tools for what's callable now, subscribe/cancel for per-MCP billing, report_bug for feedback, request_mcp for new MCPs. It also states the core flow (action=search discovers → describe returns full profile → invoke RUNS) and notes that writes require workspace owner/admin. This is far more than a typical description.

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 little beyond the annotations. It mentions including the conversation array for reproduction, which gives some context about expected input, but it does not disclose side effects, confirmation, or post-submission behavior. It does not contradict 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 extremely concise, consisting of two short sentences. It directly states the purpose and gives a key instruction without any redundant or verbose content. The structure is clean and efficient.

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 and the annotations, the description is incomplete. It does not explain the expected format of the 'conversation' field, what 'context' should contain, or any constraints on the input. It also omits any information about the return value or confirmation of submission.

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 defines parameters (context, message, conversation) but the description provides no explanation for any of them. It mentions 'conversation array' but the schema declares conversation as a string, which could cause confusion. No parameter is clarified, leaving the user to guess their meaning and format.

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: reporting a bug, missing feature, or sending feedback. It is a specific verb-resource combination and implicitly distinguishes from sibling tools like authenticate or connect, though it does not explicitly contrast them.

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 no guidance on when to use this tool versus alternatives. It does not specify scenarios such as encountering an error or needing to submit feedback, nor does it mention any exclusions or preferred contexts.

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, idempotentHint, and destructiveHint, which cover safety. The description adds no extra behavioral context like output format or dependencies, but it does not contradict the annotations either.

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, front-loaded sentence with no unnecessary words, perfectly matching the tool's simplicity.

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 parameter-less tool with rich annotations and no output schema, the description adequately conveys the purpose. It could specify what format the version info returns, but that is not critical for a version check.

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 parameters, schema coverage is trivially 100%, and the baseline is 4. The description does not add parameter-specific details, but none are 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 shows MCP platform and adapter versions, using a specific verb ('Show') and resource. It is distinct from siblings like 'toolkit_info' which likely provides broader 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?

No guidance is given on when to use this tool versus alternatives. There is no mention of 'use this when you need version info' or contrast with similar tools like 'toolkit_info'.

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=false, establishing a safe read operation. The description enriches this by detailing exactly what state information is returned (MCPs, status, accounts, tool counts), which goes beyond the annotations and gives the agent a clear picture of the return content.

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 that is front-loaded with the verb 'Returns' and packs all relevant details efficiently. No wasted words; every element contributes 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 tool with no parameters and no output schema, the description provides sufficient detail for an agent to understand its exact purpose and expected return. The scope of the tool is fully covered without any noticeable gaps.

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 baseline is 4. The description fully compensates by explaining what information the tool provides, leaving no ambiguity about the tool's function despite the absence of parameters.

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 names the resource ('current toolkit state'), enumerating the exact information provided (installed MCPs, connection status, accounts, catalog tool counts). This unambiguously differentiates it from sibling tools like connect, authenticate, or show_version.

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 that this tool is for querying toolkit state, which is distinct from the action-oriented siblings (connect, authenticate). However, it does not explicitly state when to use this tool over others or mention exclusions, though the context signals make the intended use evident.

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, destructiveHint=false, and idempotentHint=true. The description adds meaningful context beyond these: no platform credentials required, pay-per-query prepaid billing model, data is non-confidential public data, and LGPD controller responsibilities. The payment model in particular is valuable operational info that would affect whether an agent warns the user about cost. No contradiction between description and 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 core function is front-loaded ('Consulta em fonte oficial'), which is good, but the rest is a dense run-on mixing legal, commercial, and platform details into a single paragraph of clauses. Every sentence carries some information, but the structure forces the reader to untangle functional purpose from compliance disclaimers. Could be broken up or pruned.

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 output schema and no description of return values, the agent has no idea what data the query returns (case status, parties, movement history, etc.) or what 'grau' filters. The description heavily over-indexes on legal compliance while under-specifying the functional contract. For a tool with a single required parameter and no documented response, more functional detail is expected despite needing to cover its legal bases.

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 adds no clarification for either parameter. While 'numero_processo' is reasonably self-explanatory, 'grau' (court instance/degree) is a domain-specific Brazilian legal term whose allowed values and format are never clarified. With zero schema coverage and no compensation in the description, the agent is left to guess at the semantics of an ambiguous optional 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 identifies the tool's purpose: 'Consulta Processual' (case lookup) against 'Tribunal TRT5' (the 5th Region Labor Court), specifying a concrete verb+resource. However, the purpose is somewhat diluted within compliance/commercial boilerplate about LGPD and prepaid credit, and there's no explicit sibling differentiation (though siblings are all system tools, making confusion unlikely).

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 implicitly scopes usage: it queries non-confidential, citizen-accessible data from official Brazilian sources, for which the client is the LGPD data controller with legitimate purpose. This implies appropriate use cases (lawful public record lookups) but never explicitly states when to use this tool over an alternative or specifies exclusions. The guidance is present but implied rather than direct.

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