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web_search

Google web search — organic results, answer box, knowledge graph as JSON. Free 20/day, then pay-per-call via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query
glNoCountry code, e.g. us, fr
hlNoLanguage code, e.g. en, fr
numNoNumber of results (default 10)
pageNoResults page (default 1)

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the free-tier quota and pay-per-call pricing model, which is genuinely useful cost context. However, it doesn't describe what the JSON response contains beyond the listed result types, error behavior, or rate-limit specifics. The disclosed quota info is solid but the description is thin on other behavioral traits (e.g., pagination semantics, degradation under heavy use).

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

Conciseness4/5

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

Two sentences with no filler. The core search behavior is stated first, and the pricing constraint is appended as a second sentence. Brief and informative, though the pricing detail might be more useful after scope and usage context; structurally it is still clean and front-loaded on the primary purpose.

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

Completeness4/5

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

For a search tool with 100% schema coverage and no output schema, the description covers the behavior, the result types, and the cost model. The return value shape is only partially specified (mentions JSON and the result types) but no output schema is provided, so the description is doing reasonable work there. Missing error-handling and explicit alternative routing, but adequate for typical search invocations.

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

Parameters3/5

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

Schema description coverage is 100% for the five parameters, so the schema and description together fully document 'q', 'gl', 'hl', 'num', and 'page'. The description adds the pricing/quota context that the schema does not carry, which is a real increment. But it doesn't add semantic nuance beyond what the schema already states — no formatting, defaults, or interplay hints. Baseline 3 is correct given full schema coverage.

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 verb ('Google web search') with a clear resource, and enumerates the result types delivered (organic results, answer box, knowledge graph). This distinguishes it well from its sibling tool 'scrape' — one searches, the other scrapes a page. The scope is unambiguous.

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

Usage Guidelines3/5

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

It identifies the search domain and output format, which implies when to reach for it, but it does not explicitly state when to avoid it or when to use the sibling 'scrape' instead. The distinction between search and scrape is reasonably inferable, but the description does not proactively route the agent.

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

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TDQS

A3.9/5.0
Disambiguation5/5

The two tools are completely distinct: scrape fetches and converts specific URLs to markdown, while web_search performs web searches and returns structured results. There is no possible ambiguity between them.

Naming Consistency5/5

Both tool names are single verbs in lowercase snake_case: 'scrape' and 'web_search'. They follow a consistent imperative pattern, making the naming predictable and intuitive.

Tool Count3/5

With only 2 tools, the server feels thin for its apparent domain of web data access. While it covers the two most common operations, it borders on being too sparse for a comprehensive server.

Completeness4/5

The set covers the core workflows of searching the web and retrieving page content. Minor gaps exist, such as no HTML saving or link extraction, but the primary use cases are fully addressed, so it is not severely incomplete.

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