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0pen1
by 0pen1

bing_search

Execute Bing searches and receive structured JSON results with market, geo, pagination, and safe-search options.

Instructions

Run a Bing search via Scrapingdog (/bing/search). Returns parsed Bing results as JSON. Supports market/country targeting, geo coordinates, pagination, and safe-search filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ccNoTwo-letter ISO country code, e.g. 'us', 'de', 'gb'.
latNoGPS latitude for the search starting point.
lonNoGPS longitude for the search starting point.
mktNoMarket as <language>-<country>, e.g. 'en-US'. Mutually exclusive with cc.
countNoResults per page, 1–50 (actual may vary).
firstNoStarting position of organic results. Default: 1. first=10 puts the 10th result first.
queryYesThe Bing search query. Supports NOT, OR, site:, filetype:, near:, etc.
api_keyNoOverride the configured Scrapingdog API key for this call. If omitted, the key is read from SCRAPINGDOG_API_KEY or a local .env file.
filtersNoAdvanced filter string copied from a Bing search URL.
safeSearchNoAdult-content filter level.
Behavior3/5

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

With no annotations, the description carries the burden but only discloses that it returns parsed JSON and uses Scrapingdog. It does not mention auth requirements (e.g., requiring an API key), rate limits, error behavior, or that parameters like count may vary. This is adequate but lacks rich behavioral context.

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?

Two sentences, front-loaded with the action, and no waste. It effectively covers the tool's purpose, key capabilities, and return type in a compact form.

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 10 parameters and no output schema, the description is reasonably complete by summarizing the tool's scope. However, it does not detail the exact structure of the JSON response or mention operational aspects like API key handling, which the schema partially covers via the api_key parameter. It could be more precise about pagination semantics, but the schema descriptions fill most gaps.

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 coverage is 100% with detailed parameter descriptions, so the baseline is 3. The description adds a concise summary of features (market/country, geo, pagination, safe-search) that maps to existing parameters but does not introduce new meaning beyond the 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 clearly states the tool runs a Bing search via Scrapingdog, returning parsed JSON results. This distinguishes it from sibling search tools (google_search, duckduckgo_search, baidu_search) with a specific verb and resource.

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 context on supported capabilities (market/country targeting, geo, pagination, safe-search) but does not explicitly say when to use Bing over alternatives or when not to use it. No exclusions or alternative naming, but the purpose is clear enough for basic selection.

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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