GCP Billing

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

Explains side effects: config setup leads to permanent non-expiring connection, while token paste is session-only. Clarifies that calling with no args returns a link. This adds context beyond annotations (which already include idempotentHint: true). It doesn't cover error cases but adequately discloses 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 information-dense but organized as a single run-on sentence. It front-loads the purpose and provides practical usage notes. Slightly could be broken into clearer sentences, but it remains efficiently communicated.

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 it's a simple one-parameter authentication tool with no output schema, the description covers the needed context: flow, arguments, and side effects. It could mention what the response looks like (though not required), but is complete enough for an agent to use 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 schema only defines 'token' as a string with no description, so the description fully compensates by explaining the expected JWT format, the use of the token parameter, and the behavior when omitted (no args returns link). This adds significant 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 tool's function: authenticate for MCP.AI by logging in via browser and copying an access token. It specifies the two modes (config-based permanent and session-based) and how to invoke each. Though it doesn't explicitly differentiate from sibling tools, the purpose is unambiguous and distinct.

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 guidance on when to use config-based vs session-based login and how to obtain the link with no args. It could be improved by mentioning when not to use this tool or if alternatives like 'connect' might be relevant, but the usage context is well explained.

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 description's job is lighter. It adds value by explaining the conditional behavior (returns connect_url when credentials are missing, otherwise authenticated:true), which is beyond what annotations convey.

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, no redundancy, front-loads the core purpose. Every sentence provides useful behavioral detail (the two outcomes). No wasted words.

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 parameters/annotations and no output schema, the description covers the essential return values and conditional behavior completely. The tool is simple, and the description fully captures its 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?

The tool has zero parameters)Skip the schema coverage clause — with no params, the baseline is 4. The description adds meaning by explaining what the response will contain under different states, which is the only relevant semantic content for a param-less tool.

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 'Returns connection status and URLs' — a specific verb and resource. It distinguishes itself from sibling tools like authenticate and marketplace by focusing on connection status detection.

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 explains the two scenarios (all connected vs. missing credentials) and what each returns, which implies when checking connection status is appropriate. It doesn't explicitly name alternatives or say when NOT to use it, but for a status-checking tool the context is fairly unambiguous.

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 establish readOnly and idempotent behavior menu, so the description only adds 'compact totals only' which clarifies the output granularity. This is mild added value, not rich behavioral context. 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 single, focused sentence that states purpose and output characteristics. It is front-loaded and avoids unnecessary details, making it highly concise 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 has 4 parameters, no schema description, and no output schema, the description leaves significant gaps. It does not explain parameter formats, defaults, or interactions, nor does it mention any limitations. Only the basic purpose is covered, which is insufficient for full operational 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?

Schema description coverage is 0% and the description does not explain any of the four parameters (account, end_date, days_back, start_date). It mentions grouping dimensions but not the filtering parameters. With no compensation from the description, parameter semantics are virtually absent.

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 'Query' and names the resource ('normalized GCP Billing BigQuery export') and the grouping dimensions (day, service, project, SKU). It clearly distinguishes from siblings like gcp_billing_top_services by specifying the full cost breakdown.

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 (to get detailed cost breakdowns) and gives a clear context for cost analysis, but does not explicitly state when not to use it or mention alternatives. Since siblings are not referenced, it falls short of a 5 but meets the 'clear context' bar.

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 that the records are 'GCP Billing BigQuery export credential records' and scoped to the install, complementing the readOnlyHint=true annotation. It does not contradict any 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?

Single, efficient sentence with no filler, perfectly sized for the information conveyed.

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 list with one optional parameter and no output schema, the description covers the essential scope. Could mention return format but not required for this type of 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 description and schema provide no information about the 'account' parameter (0% schema coverage) and the description doesn't mention parameters, leaving the agent without guidance on filtering or expected 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 uses the specific verb 'List' with the resource 'GCP Billing BigQuery export credential records linked to this install,' clearly distinguishing it from siblings like gcp_billing_cost or gcp_billing_top_services.

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 context that the tool is scoped to the current install but does not explain when to prefer it over alternatives or when not to use it. The usage is implied but not explicit.

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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description adds some value by mentioning the BigQuery billing export source and normalized service totals. It does not contradict annotations. However, it omits details like default date behavior or whether an account context is required, so it provides only moderate transparency beyond 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 with no filler words, making it concise and easy to parse. It earns its place by conveying the core purpose and return type. It is not verbose, though it could have added more value with parameter or usage details without becoming 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?

With five parameters, no parameter descriptions, and no output schema, the description is not complete enough for reliable invocation. It mentions 'normalized service totals' but does not define the output shape or clarify how dates, limit, and account interact. The description covers the tool's idea but leaves too much operational context unspecified.

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% parameter description coverage, and the description does not explain the five parameters. 'Top' weakly hints at the 'limit' parameter, and 'from the user's BigQuery billing export' loosely relates to 'account', but start_date, end_date, and days_back are completely unexplained. The description fails to compensate for the missing schema-level parameter guidance.

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 a specific action: 'Query top GCP services by cost from the user's BigQuery billing export.' It also describes what is returned ('normalized service totals'), giving a clear sense of scope and output. However, it does not explicitly contrast with sibling tools like gcp_billing_cost, so it is not fully differentiated.

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?

There is no explicit guidance on when to use this tool versus alternatives such as gcp_billing_cost or gcp_billing_list_accounts. The phrase 'from the user's BigQuery billing export' implies a prerequisite but does not state conditions or exclusions. Usage context is only weakly implied, not articulated.

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 numerous behavioral traits beyond the minimal annotations: invoke runs MCPs one-off without toolkit modification, returns connect/checkout links for auth/payment, and requires owner/admin for writes. It also explains the distinction between installed_in_toolkit vs installed_in_workspace. These details are critical for correct usage and fully leverage the openWorldHint. 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 long but each sentence adds substantial value. It is structured with sections ("Core flow", "KEY:", "Use install only...") that improve readability. While length is justified given the 14 actions, it could be slightly more scannable, but there is no redundancy or 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?

For a highly complex tool with 14 actions and no output schema, the description covers return behaviors (links for auth/payment, installed flags, shareable prompt link), permission requirements, and distinguishes all actions. It provides enough context for an agent to select and invoke correctly, including the prompt library capabilities.

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 description explains the core parameters (action, query, mcp_id, tool_id, arguments) within the flow, but many parameters (e.g., prompt_vars, cancel_reason, prompt_targets) are not covered. With 23 parameters and 0% schema description coverage, the description only partially compensates by clarifying the key action-dependent parameters but leaves many undocumented for the agent.

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 marketplace and the way to run MCPs, covering both catalog search and execution. It distinguishes itself from sibling tools by explicitly stating its core flow (search→describe→invoke) and its unique capability to run MCPs without installation. The purpose is highly specific and well-articulated.

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?

Extensive usage guidance is provided: it explains when to use invoke vs install ("prefer invoke for a single/occasional use"), when to use list_tools, and how to handle auth/payment scenarios. It also names alternatives like install and list_tools, and clearly states the permission requirements for writes. This is explicit and actionable.

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 idempotentHint=true and destructiveHint=false, so the safety profile is clear. The description adds the instruction to include conversation for reproduction, which hints at a need for context but does not disclose further behavioral details like side effects or required authentication.

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 concise sentences, front-loaded with purpose and a key usage hint. No fluff or redundant details.

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 incomplete for a 3-parameter tool with no output schema and 0% schema documentation. It only partial explains 'conversation', omitting the essential 'message' and 'context' fields, leaving the agent guessing how to provide them.

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 only mentions the 'conversation' parameter, leaving 'message' (the actual report content) and 'context' unexplained. This is insufficient for an agent to correctly fill all 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 purpose: report a bug, missing feature, or feedback, using a specific verb ('report') and resource ('bug/feedback'). It is distinct from sibling tools which are unrelated (auth, billing, 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 usage—when a bug or feedback is encountered—but gives no explicit guidance on when not to use or alternatives. It mentions including conversation for reproduction, which hints at context but lacks exclusions or 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read-only operation. The description confirms the read-only nature by 'Show', but adds no additional behavioral context beyond the annotations. It does not describe what 'versions' includes or any potential side effects, but given the annotations, the description 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, clear sentence. It is concise and front-loaded with the verb 'Show' and the object 'versions'. No unnecessary words, perfectly sized.

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, zero parameters, no output schema, and the presence of read-only and idempotent annotations, the description is nearly complete. It explains what the tool does, and the annotations cover safety. It does not detail what the version output structure looks like, but that is not strictly necessary. The description is sufficient for a simple version check 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, and the schema coverage is 100% (no properties). The description correctly implies that no parameters are needed. This is a baseline 4 as per the rubric for tools with no 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 what the tool does: 'Show the current MCP platform and adapter versions.' This is specific and differentiates from siblings that focus on billing, authentication, or reporting. However, it does not explicitly differentiate from 'toolkit_info' which might also show version 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 on when to use this tool vs alternatives. The description only states what it does, not when it should be used. There is no mention of exclusions or alternatives, but the sibling tools like 'toolkit_info' might be an alternative, yet no explicit comparison is made.

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, destructiveHint=false, so the safety profile is covered. The description adds value by detailing what exactly is returned (installed MCPs, connection status, accounts, catalog counts), which goes beyond the annotation. It doesn't contradict annotations, so no issue.

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 packs all relevant information without any fluff. Every clause adds value: installed MCPs, connection status, accounts, catalog tool counts. Zero wasted words.

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 with no parameters and no output schema. Given the low complexity and rich annotations, the description fully covers what the tool does and what it returns. No gaps apparent.

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 baseline is 4 per the rubric. The description provides no parameter info because none exist, which is appropriate. No additional semantic is 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 returns a specific set of information (installed MCPs, connection status, accounts, catalog tool counts) using a specific verb ('returns') and resource ('toolkit state'). It is distinct from sibling tools like gcp_billing_* and authenticate, 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 implies usage: when you need to know the current toolkit state lock. It doesn't explicitly state when not to use it or list alternatives, but given the zero-parameter nature and clear scope, the context is sufficient. A 4 is appropriate for clear context without exclusions.

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