Processos TJ (Tribunal de Justiça)

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

Annotations already declare idempotentHint true, readOnlyHint false, and destructiveHint false. The description adds useful behavioral context: token permanence vs session-only, and the behavior of returning a link when called with no arguments. It doesn't contradict annotations, though it doesn't fully disclose server-side storage or expiration details.

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 wordy but contains no wasted sentences; it's organized into two main options and gets to the point quickly. It could be tightened but is appropriately sized for the information it conveys.

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 simple parameter set and no output schema, the description covers both usage modes, the context for IDE agents, and the token types. It could mention potential errors or expiration details, but it is largely complete for an agent to invoke the 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 coverage is 0%, so the description carries the full burden. It explicitly explains the 'token' parameter as a JWT to paste for session login, and the no-args call to get a link. This fully compensates for the schema's lack of descriptions and adds critical meaning.

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: to authenticate an IDE agent by logging in via browser and obtaining an access token. It distinguishes from sibling tools like 'connect' by focusing specifically on the authentication process and offering two distinct modes (permanent config vs session token).

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 provides explicit when-to-use guidance: recommends the best approach (config header for permanent connection) and describes the alternative (paste token for session-only). It also explains when to call with no args to obtain the login link, giving clear context and alternatives.

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 cover read-only, idempotent, and non-destructive behavior. The description adds valuable detail about response states (authenticated:true with empty pending[], or connect_urls), which goes 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 uses three concise sentences, front-loaded with the core purpose followed by conditional behaviors. Every sentence adds necessary information without 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?

With no output schema, the description fully explains return values for both success and missing-credentials cases. It covers the binary condition completely, making it comprehensive for this simple 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 zero parameters, so the baseline 4 applies. The description needs no parameter details, and the schema is trivially complete.

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, with explicit scenarios for all-connected vs missing-credentials. This distinguishes it from siblings like 'authenticate' by focusing on status rather than initiating auth.

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 for checking connection status, but it does not explicitly say when to use it versus alternatives like 'authenticate'. The context is clear but lacks direct guidance on selection.

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?

Discloses key behaviors beyond annotations: invoke runs tools even when the MCP is not installed, does not bloat the toolkit, returns connect/checkout links when credentials or payment are needed, and install makes permanent changes. The description also notes that search/describe flag installation status. This richly supplements the bare 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 long and dense, covering many sub-actions, but it is a single unbroken paragraph with no formatting. Every sentence adds value, but readability suffers; a structured list of actions and flows would improve scannability 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 23 parameters and no output schema, the description covers the core workflow, install/invoke differences, permission requirements, payment/auth behaviors, and the prompt library. It is missing explicit return-value details and some parameter specifics, but overall it gives a comprehensive operational understanding for such a complex 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?

Schema has 0% per-parameter descriptions, so the description carries the burden. It explains the action enum values in detail (search, describe, invoke, install, subscribe, cancel, etc.) and mentions mcp_id, tool_id, arguments, prompt_vars, and more. However, many parameters (limit, query, immediate, tier_slug, cancel_reason, etc.) are left to name inference, leaving some gaps.

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 is the official mcp.ai marketplace catalog and the way to run MCPs, listing concrete capabilities (search, describe, invoke, install, prompts). It distinguishes from siblings by being the central hub for MCP discovery and execution, but its verb is broad and multi-purpose rather than a single specific 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?

Provides an explicit core flow (search → describe → invoke), clear guidance on when to use invoke vs install ('prefer invoke for a single/occasional use'), and permissions context (writes require workspace owner/admin). Also explains auth and payment link handling, giving the agent concrete decision paths.

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 define readOnly/destructive/idempotent hints; description adds the need to include conversation for reproduction. It does not describe what happens after submission or whether auth is required, but this is partially mitigated by 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?

Two short, purposeful sentences; no filler. Every sentence 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 simple three-parameter feedback tool with no output schema, the description covers purpose and the key reproduction data. However, it omits any guidance on the optional 'context' parameter and doesn't state return/response behavior, so 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?

Schema descriptions are absent (0% coverage). The description clarifies that 'conversation' should contain recent messages, adding meaning beyond the raw schema, but it leaves 'message' and especially 'context' unexplained, and its 'conversation array' phrasing slightly conflicts with schema's string type.

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?

Description explicitly states 'Report a bug, missing feature, or send feedback', naming the verb and resource. It is clearly distinct from sibling tools like authenticate, marketplace, and 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?

It gives clear context for when to use (filing a bug/feedback) and instructs to include conversation array for reproduction. It doesn't explicitly name alternatives, but no sibling tool competes for this purpose, so no exclusions are needed.

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. The description adds context that the tool returns 'current' versions for the platform and adapter, which is useful 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 a single, efficient sentence that immediately states the tool's purpose. No filler or redundancy.

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 params, no output schema, read-only), the description fully covers what an agent needs to know. It specifies exactly what version information is returned, which is complete for this kind of informational 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?

There are zero parameters, and the schema coverage is trivially 100% (empty properties). The description correctly implies no input is needed, so the baseline for zero-param tools applies without requiring additional param details.

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'), clearly distinguishing it from sibling tools like 'authenticate' or 'connect', which have 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 conveys the obvious use case—checking versions—but does not explicitly mention when to use it versus alternatives like 'toolkit_info'. Since no exclusions or competing tools are referenced, the guidance is only 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds meaningful context about the data being public, the customer being the data controller under LGPD, and the prepaid credit model. 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?

The description is a compact paragraph with three sentences: the first states the core function, the second covers payment/hosting, and the third addresses data privacy. No filler, well-structured, and front-loaded with the main 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?

With 7 parameters, no output schema, and no parameter descriptions, the description is incomplete. It covers the tool's purpose, payment, and data privacy but does not explain the return value format, the 'completo' flag, or error behavior. For a query tool, this is a noticeable gap.

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 names the main filter parameters (CPF, CNPJ, nome da parte, número do processo, grau, UF), which helps, but it does not explain the optional 'completo' parameter or provide value formats/constraints. The parameter names are self-explanatory, but the description adds only marginal meaning beyond the 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 verb 'Consulta' (queries) and the resource 'processos no Tribunal de Justiça estadual', also specifying the query dimensions (CPF, CNPJ, nome da parte, número do processo, grau, UF). This distinguishes it from the generic sibling tools (authenticate, connect, etc.).

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 clear context: no credentials needed, paid per query, and it is for public-access data only. It implicitly guides the agent to use this for court process lookups, though it does not explicitly name alternative tools or state when not to use it. Sibling tools are unrelated, so differentiation is less critical.

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 safety profile is covered. The description adds behavioral context by detailing the exact information returned (installed MCPs, connection status, accounts, catalog tool counts), which is useful for an agent deciding to call it. 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 a single, well-structured sentence that lists all key output components without filler. Every phrase adds value, and the information is front-loaded with the verb 'Returns'.

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?

This is a simple read-only tool with no parameters and no output schema. The description fully specifies what the tool returns, making it complete for an agent to understand the tool's purpose and output. No additional context is necessary.

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 input schema fully covers this aspect. According to the rubric, a baseline of 4 applies when there are no parameters, and the description does not need to add parameter semantics. It appropriately focuses on the return content instead.

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 with a specific verb ('Returns') and lists precise content: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate or 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 implies the tool is for retrieving toolkit state, but it does not explicitly say when to use it over alternatives or mention any exclusions. The usage context is clear but only implied, not explicitly stated.

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