Crawdar Business Research

Test the Crawdar contract

sandbox_businesses

Read-onlyIdempotent

Return deterministic fictional businesses without consuming provider capacity. Use this to test schemas, clients, and agent loops.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`target`	No	Fictional business type echoed into deterministic test results.
`geography`	No	Fictional location echoed into deterministic test results.

Output Schema

TableJSON Schema

Name	Required	Description
`limit`	Yes	Maximum prospects requested for this page.
`offset`	Yes	Zero-based offset of this page.
`hasMore`	Yes	Whether another result page is available.
`results`	Yes
`warnings`	Yes	Limitations the agent should retain with downstream data.
`requestId`	Yes	Request identifier for support and diagnostics.
`durationMs`	No
`nextOffset`	No	Offset for the next synchronous result page, or null when complete.
`diagnostics`	No	Source status and explained candidate exclusions.
`resultCount`	Yes	Total accepted prospects before response pagination.
`returnedCount`	Yes	Prospects returned in this response page.
`schemaVersion`	Yes	Version of the result contract.
`searchedSources`	Yes	Discovery and first-party source types consulted.
`remainingFreeSearches`	No

TDQS

A4.3/5.0

Behavior4/5

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

The description adds meaningful behavioral context beyond annotations by disclosing that results are deterministic, fictional, and do not consume provider capacity. This complements the readOnlyHint and idempotentHint annotations without contradicting them.

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 efficient sentences convey the core behavior and intended use immediately. There is no filler, and the most important distinguishing information is front-loaded.

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 a rich output schema, clear annotations, simple optional parameters, and a purpose-specific description, everything needed for correct use is present. The tool's scope is intentionally narrow and the description fully covers it.

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%, so parameters are already fully documented in the schema. The description does not add new parameter-specific meaning beyond reinforcing that the parameters echo into deterministic results, which the schema already states.

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 a specific action ('Return deterministic fictional businesses') and identifies the tool's purpose as testing schemas, clients, and agent loops. It distinguishes itself from sibling tools like research_businesses and search_businesses by emphasizing deterministic fictional data and no provider capacity consumption.

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 explicitly says 'Use this to test schemas, clients, and agent loops,' providing clear context for when to use the tool. It implies the tool is for sandbox testing rather than production lookups, though it does not explicitly name alternative tools or state exclusion conditions.

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

All Crawdar Business Research tools Inspect

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TDQS

A4.4/5.0

Disambiguation4/5

Most tools map to distinct lifecycle actions (start/get/cancel/refine/retry), and the descriptions make those boundaries clear. The only real overlap is between research_businesses and search_businesses, which both perform synchronous lookups but are separated by natural-language vs structured input.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern, with lead_search reused across lifecycle operations. Even explain_crawdar and sandbox_businesses fit the naming convention well.

Tool Count5/5

Nine tools is well within the appropriate range for a business-research MCP server. The count balances synchronous search, a durable async job lifecycle, sandbox testing, and self-documentation without feeling bloated.

Completeness4/5

The async lead-search lifecycle is well covered with start, get, cancel, refine, and retry, and the synchronous and sandbox search tools cover adjacent needs. However, export is mentioned in start_lead_search but not exposed as a tool, and there is no way to list existing jobs, leaving minor gaps.

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