TCU (Licitante Inidôneo)

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

The description adds context beyond annotations by explaining two authentication modes: a permanent non-expiring connection via config header, and a session-only login via token. It also notes the tool returns a link when called with no args. This enriches the behavioral understanding without contradicting the idempotent and non-destructive 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 three sentences and front-loaded with the purpose. It is reasonably concise, but the phrasing 'log in in the browser' is slightly awkward and the config-header explanation could be more streamlined. Overall it is structured and each 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?

Given the simple one-parameter schema and no output schema, the description covers the primary use cases: permanent config vs. session token, and the no-args behavior. It lacks details on error responses or token validation, but these are not critical for an authentication tool. The description is complete enough for an agent to invoke it 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?

The input schema only defines 'token' as an optional string with no description. The description fully compensates by explaining exactly how to use it: 'call with { token: "<jwt>" } after the user pastes' and what happens when omitted ('with no args to get the link'). This provides complete parameter semantics.

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 states the tool authenticates the user, with a clear process: 'log in in the browser, copy the access token.' It defines the resource (authentication) and the verb (authenticate). However, it does not explicitly distinguish this from the sibling tool 'connect', so it misses the top score for sibling differentiation.

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 guidance: call with no args to get a link, or pass a JWT token for session-only login. It also explains when to prefer the permanent config header approach over the session method. It does not mention alternatives like 'connect', 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?

Annotations already declare readOnlyHint and idempotentHint. The description adds conditional behavior (authenticated:true with empty pending[] when all providers connected, connect_url when credentials missing), which is useful beyond the annotations. It does not cover partial-connection states, leaving some gaps.

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 and conditional details. Every sentence earns its place without 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?

The description explains two primary scenarios but omits partial-connection cases and doesn't elaborate on the structure of URLs or pending[] beyond what's mentioned. Given no output schema, this leaves some ambiguity about the full set of possible responses.

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, so the description has no parameter burden. Per the rubric, 0 params yields a baseline of 4.

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 'Returns connection status and URLs' and specifies conditional behavior for all-providers-connected vs. missing credentials, making it distinct from sibling tools like '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 implies this is for checking connection status, but it does not explicitly name alternatives or when not to use this tool. Siblings like 'authenticate' obviously have a different purpose, but the comparison is left implicit.

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 key side effects and preconditions: invoke runs one-off without installing, returns connect link if credentials needed, returns checkout link if wallet empty, and writes require workspace owner/admin. This goes beyond the annotations (readOnlyHint=false) and clarifies mutation, auth, and payment behavior. No contradiction 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 dense single block but logically flows from definition to core flow to key caveats to other actions to prompt library. Every sentence adds useful info for a tool with 23 parameters and 14 action values. However, it is long and could be split into structured bullets for readability, so not a 5.

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?

Despite no output schema, the description explains return behavior for critical actions (describe returns full MCP profiles with params/pricing/auth, invoke returns connect/checkout links, get_prompt returns full text with variables filled). It covers auth, billing, installation semantics, and the prompt library. For a tool representing an entire marketplace, it is nearly 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 well for core parameters: action is explained through the flow (search→describe→invoke), mcp_id/tool_id/arguments are contextualized ('pick the right tool_id', 'invoke RUNS that tool'). Prompting parameters are named. However, some parameters (limit, immediate, tier_slug, conversation, cancel_reason, etc.) remain undocumented, leaving 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 opens with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' This gives a specific noun (marketplace) and clear verbs (catalog, run). It enumerates distinct actions (search, describe, invoke, install, etc.) that differentiate it from siblings 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?

Explicit guidance is provided: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'; also says 'invoke works even when the MCP is NOT installed'. Each sub-action (report_bug, request_mcp, subscribe/cancel, list_tools, search_prompts) has a one-line when-to-use statement.

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=false and destructiveHint=false, so the safety profile is known. The description adds extra context by specifying that the conversation array should be included for reproduction, which helps the agent understand what information is expected for effective reporting.

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 sentence that immediately states the purpose and includes a key usage hint. There is no unnecessary verbiage, and the structure is ideal for quick scanning.

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 is simple, and the description covers its purpose and one parameter hint, but with no output schema and a bare input schema, it leaves gaps around the 'message' parameter, the optional 'context' field, and what happens after submission. It is adequate for basic understanding but 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?

The schema has 0% description coverage, so the description must compensate. It explains the 'conversation' parameter's purpose but says nothing about 'message' or 'context'. This leaves the required 'message' parameter and optional 'context' without semantic meaning, though the overall intent is partially clear.

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 'Report' with a clear resource ('bug, missing feature, or feedback'), which makes the tool's purpose unambiguous. It stands apart from sibling tools like 'authenticate' or 'marketplace' because none of those are about reporting issues.

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 concrete guidance on what to include ('conversation array with recent messages for reproduction'), which tells the agent what context is needed. It does not explicitly name alternative tools or exclusions, but the sibling list makes the intended use clear enough.

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 no behavioral context beyond the fact that it shows current versions. It does not describe return format, whether it performs any network calls, or what 'current' implies. With the annotated safety profile, a neutral score is appropriate.

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 wasted words. It communicates the essential purpose efficiently. Perfectly concise for a zero-parameter utility.

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 read-only version-check tool, the description provides enough to understand its function. It lacks explicit output formatting details (e.g., whether it returns JSON, a string, or a structured object), but given no output schema, this is a minor gap. The tool is not complex enough to require more.

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 0 parameters and the input schema is empty (100% coverage vacuously). The description identifies the subject (MCP platform and adapter versions) but there are no parameters to explain, so the baseline 4 for zero-parameter tools applies.

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 a clear resource 'current MCP platform and adapter versions.' It directly states the tool's function and distinguishes it from all listed siblings (authenticate, connect, marketplace, report_bug, tcu_inidoneo_consultar, toolkit_info), none of which are about showing versions.

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 when to use (when version information is needed) but does not explicitly discuss conditions, exclusions, or alternatives. While no sibling overlaps, there is no stated 'use this for...' or 'instead of...' guidance. The utility is straightforward, but the tool description remains silent on 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable context: hosted platform, no credentials, prepaid credit, public data source, and LGPD compliance. This goes beyond the annotations by explaining the transactional and legal nature of the operation, though it does not describe the response format or error 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 sentences with no redundant information. It front-loads the core purpose and efficiently adds distinguishing context (payment, public access, legal responsibility). Every sentence contributes value, and it is appropriately sized for the tool's complexity.

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 essential context: what the tool does, who it is for, the data type (public), the access model (no credentials, prepaid), and legal compliance (LGPD). It does not describe the output format or edge cases, but there is no output schema to rely on. For a focused consultation tool, the coverage is quite good, though a brief note on what 'completo' returns would make it 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 description coverage is 0%, so the description must compensate. It explains that CPF and CNPJ are used to identify the person or company, covering the two required parameters. However, the optional 'completo' parameter is not explained at all. Additionally, the description says 'a partir do CPF ou CNPJ' (either one), while the schema requires both Cpf and Cnpj, creating ambiguity. Partial compensation, but incomplete.

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: 'Emite a certidão negativa de licitante inidôneo no TCU para uma pessoa ou empresa a partir do CPF ou CNPJ.' This specifies the verb (emite/emits), the resource (certidão negativa), and the audience (person/company via CPF/CNPJ). It is clearly differentiated from sibling tools, which are all generic platform utilities (authenticate, connect, marketplace, 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?

The description provides clear usage context: it explains the commercial model (pay-per-query with prepaid credit), that no credentials are needed, and that the queried data is public. It does not explicitly name alternatives, but the sibling tools are unrelated, so no exclusions are necessary. The guidance is sufficient for a specialized consultation 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context by specifying exactly what information is returned (installed MCPs, status, accounts, tool counts), enriching the behavioral understanding 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, front-loaded sentence that conveys all essential information without any filler. Every word contributes meaning, making it highly concise and well-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 simplicity of the tool (no parameters, no output schema), the description fully covers what the tool does and what it returns. It lists the key components of the toolkit state, making it complete for an AI agent to use 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?

The tool has zero parameters, so there is no need for parameter-level detail. The schema coverage is trivially 100% with an empty object, and the description correctly focuses on the return value rather than 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 uses a specific verb ('Returns') and clearly specifies the resource ('current toolkit state') with enumerated content (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate, connect, and marketplace, which serve 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 clearly implies this is the tool for inspecting toolkit state, and the sibling tool names show no overlap. However, it does not explicitly state when to use it over alternatives or provide exclusions, so it falls short of full guidance.

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