Server Quality Checklist

Tool Scores

• searchA
  4.7/5.0
  Behavior5/5

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

  The annotations already establish read-only, open-world, idempotent, non-destructive behavior, and the description adds valuable context on top: Google's total_results can shrink while paging, corrected_query does not change the actual results, each call consumes one unit of a daily quota, and engine coverage depends on the control-panel configuration. These details go well beyond the structured hints and help an agent predict real behavior.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is long but every sentence carries distinct information: return fields, pagination, quota, coverage caveats, and the Search Console distinction. It is front-loaded with the core purpose and follows with operational constraints. No sentence is filler or redundant with the schema.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  With no output schema, the description compensates by enumerating the returned fields and their caveats. For a 20-parameter tool with one required parameter, it covers what results look like, how pagination works, quota implications, and engine coverage. An agent has enough context to invoke it correctly without guessing.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so the baseline is 3, and the description still adds meaning beyond the schema: it explains the next_start pagination mechanism, the 10-per-call/100-per-query limits, and the cost of each call against the quota. This is useful semantic context for choosing parameter values, though the schema itself already documents each parameter well.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description opens with a specific verb and resource: 'Web search through your Google Programmable Search Engine (Custom Search JSON API).' It clearly conveys this is a web search tool returning query metadata and result items, which distinguishes it from the sibling image search and from Google Search Console. The explicit 'NOT Google Search Console' note further sharpens the boundary.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  It provides clear operational guidance: paginate with next_start, stay within the 100-result window, and prefer one precise query because each call consumes quota. It explicitly says the tool cannot report how your own site is indexed or ranked, a useful when-not-to-use exclusion. It does not explicitly route to search_images or raw_request, so it stops short of naming alternative sibling tools.

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

• search_imagesA
  4.7/5.0
  Behavior5/5

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

  Beyond the readOnly/idempotent annotations, the description reveals important behavior: the 400 error condition, the meaning of item.url vs image.context_url, thumbnail and size fields, quota cost, pagination behavior via next_start, and the full set of image-only filters. This is rich, non-obvious behavioral detail.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is long but every sentence earns its place. It front-loads the core purpose and the critical engine prerequisite, then covers result shape, shared behavior, and image-only filters in a logical progression. It efficiently leverages the sibling search tool instead of repeating all shared details.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with 24 parameters, no output schema, and meaningful API quirks, the description is remarkably complete. It covers prerequisites, error conditions, result semantics, pagination, quotas, shared filters, and image-specific filters, leaving little ambiguity for an agent needing to invoke it correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so the schema already documents all parameters well. The description still adds value by grouping filters, clarifying shared semantics with the search tool, emphasizing 'use rights for reusable images', and explaining pagination/quota behavior that the schema alone does not convey.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a specific operation: image search through a Google Programmable Search Engine with searchType=image. It clearly distinguishes this from the sibling 'search' tool by focusing on image-specific behavior and explicitly saying 'Everything else matches the search tool.'

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description gives clear context: use this for image search, and it requires the engine to have Image search enabled, otherwise the API returns 400. It references the alternate generic search tool for shared filters/pagination behavior, though it does not explicitly state 'use search for non-image queries'.

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

• raw_requestA
  4.9/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description reinforces these by stating 'The API has GET endpoints only, so nothing here can modify data.' It also discloses auth behavior (key added in a header, engine id auto-filled), which is valuable 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is concise but information-dense, front-loading the purpose ('Escape hatch') and then efficiently covering usage, examples, auth behavior, and safety. Every sentence contributes value.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a single-parameter escape-hatch tool, the description is complete: it specifies the path format, the base URL, the response shape, the parameter coverage gap it fills, and the safety guarantees. No output schema exists, so the description appropriately carries the burden of explaining the return envelope.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100% and the schema already documents the path parameter. The description adds meaningful context with the relative-to-base URL clarification, an example path, and side behaviors like automatic key/engine-id injection, which goes beyond the bare schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a precise verb and resource: 'performs a GET against any Custom Search JSON API path and returns the raw, unnormalized response envelope.' It also distinguishes itself from typed sibling tools by explicitly targeting parameters the typed tools do not expose.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  It gives an explicit when-to-use condition: 'Use it for parameters the typed tools don't expose (lowRange/highRange, c2coff, hq, fields).' It also provides a concrete example path and explains how the API key and engine id are handled, making the invocation context unambiguous.

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