ECAC PER: DCOMP

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

The description adds behavioral context beyond the annotations by explaining the permanent vs. session-only distinction, the non-expiring nature of the config header approach, and the no-args behavior of returning a login link. It does not describe error cases or what happens on invalid tokens, but it meaningfully supplements the annotation 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 compact and front-loaded with the tool's purpose, then efficiently explains both usage modes. It is slightly run-on with multiple clauses in one sentence, but every part adds necessary information and there is no 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?

Given the tool's simple input schema and lack of output schema, the description covers the essential context: browser login, token handling, permanent vs. session auth, and the no-args behavior. It does not describe the response format or post-auth state, but for this tool's complexity the coverage is 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%, so the description carries the full burden for parameter meaning. It explicitly explains that the 'token' parameter is a JWT to be pasted for session-only login, and that omitting the parameter returns the login link. This fully compensates for the sparse 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 an IDE agent by logging in via browser and obtaining an access token. It specifies the exact resource (MCP.AI server auth) and the action (log in / authenticate), and the browser-based flow distinguishes it from the sibling 'connect' tool.

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 usage context with two explicit modes: permanent config-based auth via Authorization header, and session-only login by passing a token. It also explains when to call with no args ('to get the link') versus with a token. However, it does not explicitly mention when not to use this tool or name alternative tools.

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 readOnly, idempotent, and non-destructive hints. The description adds useful behavioral detail beyond the schema by describing the two possible response states: authenticated with empty pending[], or missing credentials with connect_url returned.

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 long and front-loads the core function. Every sentence adds meaningful information about the operation and conditional outcomes, with no redundant 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?

For a zero-parameter status-checking tool, the description covers both primary scenarios and mentions key return fields. It is complete enough given the simple context, though it could briefly mention sibling tools like 'authenticate' for clearer workflow guidance.

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 the schema is fully documented by default. The description adds relevant context about what the result will contain, compensating for the lack of an output 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 returns connection status and URLs, with a specific verb ('Returns') and resource. It conveys the core purpose and differentiates from siblings like 'authenticate' by focusing on status reporting rather than performing authentication.

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 tool is used to check connection status and retrieve connect URLs, especially when credentials are missing. However, it does not explicitly state when to prefer this over 'authenticate' or when not to use it.

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 declare readOnlyHint and idempotentHint. The description adds valuable behavioral context beyond this: cost per query, no platform credentials, data is not confidential, and LGPD responsibilities for the client. This helps the agent understand operational and legal implications.

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 relatively short but structured as a single dense block with run-on clauses. It mixes operational details, legal terms, and data sourcing without clear separation, making it less scannable than desired.

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 a paid query with multiple parameters and no output schema, yet the description does not specify the return value, expected input formats, or the role of each parameter. It provides business context but lacks the technical detail needed for correct invocation.

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 4 parameters with zero description coverage. The description does not explain perdcomp, pkcs12_cert, pkcs12_pass, or perfil_procurador_cnpj. It only mentions that no platform credentials are needed, which is tangential and leaves the agent without essential parameter 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 identifies this as a query tool for DCOMP data from official Brazilian sources. The verb 'consultar' in the name and 'consulta' in the description make the purpose explicit, and it is distinctly different from sibling tools like authenticate or 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 provides clear context on when to use this tool: it requires prepaid credit, does not use platform credentials, and is a hosted official source query. It doesn't explicitly discuss alternatives, but given the sibling set, no direct alternatives exist.

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?

Beyond the basic annotations, the description discloses key behaviors: invoke runs uninstalled MCPs one-off without bloating the toolkit, credential requirements produce a connect link, empty wallets produce a checkout link, and the one-off install behind invoke counts as a write. It also reveals installed_in_toolkit vs installed_in_workspace flags and shareable prompt links that open without login.

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 single dense paragraph is front-loaded with the core definition and flow, and every sentence carries operational value. However, given the 14-action scope, bullet structuring or shorter phrasing would improve scannability without losing substance.

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 strong for a high-complexity tool with no output schema: it covers the marketplace lifecycle, prompt library, permissions, and credential/payment edge cases. It still omits some return-value expectations and details for actions like resume and cancel, so it is 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?

With 23 parameters and 0% schema description coverage, the description partially compensates by explaining the action workflow and the roles of mcp_id, tool_id, and the prompt_* params. However, it leaves many parameters under-specified, including arguments, immediate, tier_slug, conversation, prompt_vars, and request_details, forcing the agent to infer meaning from names and defaults.

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 and execution layer, with a concrete core flow: search discovers MCPs, describe returns a profile, and invoke runs the chosen tool. This specific verb+resource framing distinguishes it from siblings like authenticate and report_bug.

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 explicit when-to-use guidance: prefer invoke for one-off use, use install only to make an MCP permanent, and retry invoke after the user opens a connect/checkout link. It also separates the prompt library sub-flows and notes that writes require workspace owner/admin, covering alternatives and prerequisites.

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?

Annotation Contradiction: the description says 'Report a bug... send feedback,' which implies each call has a side effect (submitting a report), while idempotentHint=true claims repeated calls with the same arguments produce no additional side effects. This is a serious inconsistency, and the description adds no other behavioral details such as response behavior or retry implications.

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. It states the purpose and the key reproduction requirement, earning its length.

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 three parameters, no output schema, and a side-effecting nature, but the description only covers the conversation parameter and leaves message/context semantics undefined. The idempotency annotation conflict further undermines the agent's ability to predict behavior.

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 adds useful meaning for 'conversation' (recent messages for reproduction), but it does not clarify the 'message' or 'context' parameters, and it calls 'conversation' an array while the schema declares it a string defaulting to '[]', creating ambiguity.

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 specific verbs and a resource: 'Report a bug, missing feature, or send feedback.' This clearly identifies the tool as a user-facing reporting channel, and it is easily distinguished from sibling tools like authenticate or 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?

It states the intended use cases directly ('bug, missing feature, or feedback') and instructs the agent to include recent messages for reproduction. It lacks explicit when-not-to-use or alternative tool guidance, but the sibling set provides no close alternative, so the context is 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, fully covering the safety profile. The description adds no additional behavioral context beyond restating the action, like output format or side effects, but since annotations handle it, the bar is lower.

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 superfluous information. It front-loads the key action and object, making it immediately understandable.

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, no output schema, and comprehensive annotations, the description fully covers what the tool does. It mentions the platform and adapter versions, which is complete for the agent's needs.

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 nothing for the description to clarify beyond the schema. The baseline for zero-parameter tools is 4, and the description does not need to add parameter 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 clearly states the tool's purpose with a specific verb 'Show' and specific resource: 'current MCP platform and adapter versions'. It is distinct from sibling tools like authenticate or connect, which deal with 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 description implies usage for retrieving version information but does not explicitly mention when to use it versus alternatives or any exclusions. However, for a simple informational tool with no close siblings, the context is 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 read-only, idempotent, non-destructive behavior, so no contradiction exists. The description adds context by specifying the returned information granularity (which MCPs are installed, their connection status, associated accounts, and catalog tool counts). It doesn't explicitly note staleness or system-call behavior, but for a simple getter, the disclosure 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, information-dense sentence with the key verb upfront. It uses a colon to introduce a list of returned state elements, which is efficient. It loses a single point for the ability to be slightly more compact, though this level of detail is arguably necessary to convey the range of state covered.

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 tool with no output schema, the description provides a complete picture of the return value. It could potentially mention the default behavior, but that's a minor point. It's complete for its intended purpose.

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?

This tool has zero parameters, and schema coverage is effectively 100% at 100% per context signals. The baseline for zero-parameter tools is 4, and the description adds value by clearly enumerating the output state details, going beyond the baseline.

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?

Uses a specific verb ('Returns') with a clear resource ('current toolkit state') and enumerates the contained data (installed MCPs, connection status, connected accounts, catalog tool counts). This is readily distinguishable from its siblings by its description of a state-inspection operation; 'connect' and 'authenticate' are clearly different actions.

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 has no explicit when-to-use guidance or alternative tools. However, as an information-gathering tool, its use case is clear and largely unambiguous from the phrasing 'current toolkit state.' There is no mention of when not to use it, such as 'to modify connection status, use connect instead.'

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