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Serpapi

by io.github.pipeworx-io

Serpapi Google Shopping

serpapi_google_shopping
Read-onlyIdempotent

Search Google Shopping for <query> — returns product title, price, source, rating, reviews, product ID, and link via SerpApi. Example: serpapi_google_shopping({ q: "wireless earbuds", gl: "us", hl: "en", _apiKey: "your-serpapi-key" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesProduct search query, e.g. "wireless earbuds", "running shoes"
glNoOptional two-letter country code, e.g. "us", "gb"
hlNoOptional two-letter UI language code, e.g. "en", "fr"
_apiKeyYesSerpApi API key (get one at serpapi.com)

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that it returns specific fields but does not discuss rate limits, pagination, or error behavior. It provides some extra context but not substantial behavioral details.

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 two sentences plus an example, with no wasted words. It front-loads the core purpose and output, making it quick to parse.

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?

Given no output schema, the description lists return fields adequately. However, it does not describe the response structure (e.g., array vs. object). With full parameter coverage and good annotations, completeness is high but could be improved with output format hints.

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%, so parameters are already well-documented. The description adds value by providing a concrete example showing parameter usage and listing output fields, which helps the agent understand what to expect.

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 clearly states the verb 'Search' and the resource 'Google Shopping', and lists specific returned fields (title, price, source, etc.). It distinguishes itself from sibling tools like serpapi_google_jobs or serpapi_google_maps by explicitly targeting shopping results.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives (e.g., general web search vs. shopping-specific). The description does not mention when not to use it or compare to sibling tools.

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

A3.8/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, deep_research, and bet_research all querying data but with nuanced differences. The descriptions help but boundaries remain fuzzy, especially between ask_pipeworx and deep_research for broad vs. single lookups. Overall moderate ambiguity.

Naming Consistency2/5

Naming is inconsistent: some tools use snake_case (ask_pipeworx, ai_visibility_check), others use camelCase (serpapi_google_jobs), and patterns vary widely (e.g., pipeworx_feedback vs. compare_entities). Only the serpapi_google_* group follows a consistent pattern.

Tool Count3/5

36 tools is on the high side for a single server, with many meta-tools (discover_tools, suggest_questions) and niche prediction market tools. The scope seems overly broad, covering data lookup, prediction markets, memory, and subscriptions, which could be streamlined to a more focused set.

Completeness3/5

The server covers a wide range of domains (financial, economic, news, drugs, prediction markets, Google services), but lacks direct web search and write/update capabilities. While the coverage is broad, there are notable gaps (e.g., no generic web search, limited tool for modifying data) for a data-focused server.

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