Buscador: Google

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

Annotations indicate non-read-only (readOnlyHint false) and idempotent (idempotentHint true). The description adds context about side effects: permanent config changes vs session-only login, and the option to get a link. It avoids contradicting annotations and clarifies the two authentication modes.

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?

Three sentences, each carrying information: purpose, recommended permanent method, and session method. The first sentence is front-loaded with the core purpose. Slightly verbose but not bloated.

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 optional-param tool with no output schema, the description is complete: it covers both usage paths, prerequisites (browser login), and expected outcome (token or link). No critical gaps identified.

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 a 'token' string. The description enriches this by specifying it's a JWT and explains that omitting the argument triggers a link generation. This compensates for the 0% schema description coverage.

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 authenticates an IDE agent by logging in through the browser and obtaining an access token. It distinguishes itself from siblings like 'connect' by focusing specifically on authentication flow, though it doesn't explicitly name alternatives.

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 instructions for two methods: permanent via config header and session-only via pasting token. Explains the no-args behavior for getting a link. However, it doesn't directly contrast with sibling 'connect' or state when not to use this tool, so it's slightly below full clarity.

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 behavioral context beyond that: the tool consumes prepaid credit per query, requires no platform credentials, and the client is responsible for LGPD compliance. This billing and compliance information is not present in 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 concise and front-loaded with the core purpose. Sentences are short and each adds relevant context, though the LGPD clause is a bit dense for a search tool. It does not waste words on repetitive 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?

For a simple tool with no output schema and rich annotations, the description covers purpose, pricing, data scope, and compliance. However, it omits any explanation of the parameters, especially 'safe', and does not describe what the result of a query looks like, which would be expected without an output schema.

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 two parameters (query, safe) with 0% description coverage. The description mentions 'consulta' which hints at the query parameter, but it does not explain either parameter, especially 'safe', which remains ambiguous. With low schema coverage, the description needed to compensate and did not.

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 'Buscador: Google, consulta em fonte oficial' and later clarifies it queries information from official Brazilian sources and agencies. This specifies a clear verb+resource (query official sources) and differentiates it from the 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 provides useful context: it is hosted by the platform, requires no platform credentials, is paid via prepaid credit, and accesses the same data available to citizens. However, it does not explicitly state when to use this tool instead of alternatives or mention any exclusions, so it stops 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.

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds transparency by detailing the two possible return scenarios (all providers connected vs missing credentials), which enhances understanding without contradicting 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 concise, consisting of two sentences that clearly convey the tool's behavior without unnecessary detail.

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 provides sufficient context by explaining the return values in both possible states, making it complete despite the absence of an output schema.

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 no parameters, and the schema is complete with 100% coverage (empty properties). Since there are no parameters to describe, the baseline score of 3 is appropriate.

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 that the tool returns connection status and URLs, which distinguishes it 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?

It implies usage for checking connection status, but does not explicitly mention when to use this tool versus alternatives. The purpose is clear enough to infer appropriate 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?

Beyond the annotations (readOnlyHint=false, openWorldHint=true, etc.), the description discloses key behaviors: invoke runs uninstalled tools one-off, does not bloat the toolkit, requires credentials or payment in certain cases, and writes require workspace owner/admin. It also notes installed-in-toolkit vs installed-in-workspace flags. It lacks detail on rate limits or exact return shapes, but the additional context is substantial.

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 information-dense and front-loaded, but it is a single long paragraph with many semicolon-separated clauses and a mid-sentence Portuguese term ('pontualmente'). Every sentence mostly earns its place, but the structure makes it harder to parse than a bulleted or sectioned description would be.

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 14 actions, 23 optional parameters, and no output schema, the description is unusually complete: it explains the core search→describe→invoke flow, the install vs invoke distinction, auth/payment behavior, permission requirements, and the separate prompt-library subdomain. It still leaves some action-specific details and parameter values unexplained, but the overall picture 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%, and with 23 parameters the description carries a heavy burden. It explains several parameters implicitly (action, query, tool_id, arguments, prompt_* fields) and maps actions to behaviors, which is helpful. However, it never defines key parameters such as limit, immediate, tier_slug, conversation, message, or cancel_reason, leaving meaningful gaps for an agent trying to construct correct calls.

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 establishes the tool as the mcp.ai marketplace catalog and execution layer, covering search, describe, invoke, install, billing, and prompt-library actions. It is more than a restatement of the name and provides a concrete resource ('official mcp.ai marketplace') and actionable verbs. However, it is broad and does not explicitly differentiate itself from sibling tools like connect or authenticate.

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 strong internal usage guidance: use invoke for one-off runs, use install only when making an MCP permanent, use search/describe to discover, and use request_mcp when nothing fits. It also explains credential and payment flows ('connect link', 'checkout/top-up link', then retry). It does not explicitly contrast with sibling tools, so it stops short of a perfect 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 indicate idempotentHint=true and destructiveHint=false, so the description doesn't need to repeat those. It adds context about including the conversation array for reproduction, which is useful. However, it doesn't disclose what happens after submission (e.g., whether it creates a ticket, sends an email) or any side effects beyond 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 two sentences, front-loaded with the purpose, and includes a specific instruction. Every sentence earns its place with no 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?

Given the tool's simplicity (3 params, no output schema, no nested objects), the description is adequate but not complete. It covers the main purpose and the key reproduction instruction, but lacks details on expected outcomes or additional context for the 'context' parameter. It's a minimum viable description for a feedback 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 description coverage is 0%, so the description must compensate. It mentions 'conversation array' and 'recent messages for reproduction,' which adds meaning to the 'conversation' parameter. However, it doesn't explain 'context' or 'message' beyond what the schema provides (type and default). The description partially compensates but leaves gaps for two of three 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 clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and resource ('bug'), and distinguishes from siblings by covering feedback and missing features, which are not implied by sibling names 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 implies when to use the tool (when reporting bugs, missing features, or feedback) but does not explicitly state when not to use it or mention alternatives. It provides a usage hint by instructing to include the conversation array for reproduction, which gives context but lacks 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=true, idempotentHint=true, and destructiveHint=false, making the safety profile clear. The description adds valuable specificity by naming the exact version types returned ('MCP platform and adapter versions'), which goes beyond the generic annotations. It does not mention any side effects, authentication requirements, or output format, but for a zero-parameter simple query tool, the provided information 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 single-sentence description is succinct and front-loaded with the key verb and object. There is no filler or redundant content; every word contributes to understanding the tool's function. It is appropriately sized for a tool with no parameters.

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 (no parameters, no output schema), the description combined with annotations covers the essential information. It clearly states what versions are shown. The only minor gap is the absence of details about the return value's format (e.g., string, object, JSON), but for a version-checking tool this is not critical and can be inferred from standard conventions.

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 input schema is empty with 100% coverage (nothing to document). Per the rubric, a baseline of 4 is appropriate when there are no parameters, and the description correctly does not attempt to explain nonexistent parameters. No additional semantic value is needed for 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 clearly states the tool's function: 'Show the current MCP platform and adapter versions.' It uses a specific verb ('Show') and identifies the exact resource (platform and adapter versions). This unambiguously distinguishes it from sibling tools like authenticate, connect, or 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?

The description does not explicitly state when to use this tool versus alternatives, but the purpose is self-evident given its name and description. There is no competing tool for version retrieval among the siblings, so usage context is implied rather than explicitly stated. It lacks any when-to-use or when-not-to-use guidance, but this is a simple informational tool where the context is clear.

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=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-mutating operation. The description adds value by specifying what fields it returns (installed MCPs, connection status, accounts, catalog tool counts), which is not in the annotations. However, it does not disclose any potential side effects or behavior like caching or rate limits, but with annotations covering safety, a 3 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, concise sentence that front-loads the primary purpose ('Returns the current toolkit state') and then lists the key components. It avoids unnecessary detail and is easy to scan, though it does list multiple elements in a slightly dense list form.

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 read-only information tool with output not specified by an output schema, the description provides adequate detail about the nature of the returned data. It covers the main categories of information, though it could briefly mention that this helps diagnose connection issues. Overall, it's complete for a tool of this simplicity.

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)Skip, and the description correctly indicates that it simply returns state. The schema coverage is 100% (trivially, with no properties), so there are no param details to compensate for. The description does not need to explain parameters, as there are none.

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 that the tool returns the current toolkit state and enumerates the specific types of information (installed MCPs, connection status, accounts, and number of catalog tools). It distinguishes itself from siblings like authenticate and show_version by focusing on toolkit state rather than authentication or version details.

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 for checking toolkit status, but it does not explicitly state when to use it versus other tools. For example, it doesn't mention that it should be used to verify connections before using tools or when troubleshooting failures. Sibling names like authenticate and connect suggest distinct purposes, but the description offers no explicit usage context.

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