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research

Conduct comprehensive web research on any topic or question by initiating cloud-based investigations that gather and analyze information from multiple sources.

Instructions

Run a deep research investigation on a topic or question. Requires WEBCLAW_API_KEY. Starts an async research job on the webclaw cloud API, then polls until complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoEnable deep research mode for more thorough investigation (default: false)
queryYesResearch query or question to investigate
topicNoTopic hint to guide research focus (e.g. "technology", "finance", "science")
Behavior3/5

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

Discloses async execution model (starts job, polls) and authentication requirement, which is valuable given no annotations. However, missing critical behavioral details: no description of return format (text? JSON? report?), no mention of rate limits, cost implications, or error states for the cloud API operation.

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?

Three sentences with zero waste: purpose front-loaded, prerequisites stated, execution model explained. No redundancy with structured fields.

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

Completeness3/5

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

Adequate for basic invocation but gaps remain: no output schema exists yet description doesn't specify return format (critical for a research tool), and lacks guidance on expected duration or result structure given the async polling pattern described.

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 has 100% description coverage, establishing baseline 3. Description reinforces parameters by mentioning 'deep research' (deep), 'topic' (topic), and 'question' (query), but adds no syntax details, examples, or constraints beyond what the schema already provides.

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

Purpose4/5

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

Clear verb+resource ('Run a deep research investigation') and distinguishes from siblings like 'search' by emphasizing 'deep' investigation and async execution ('polls until complete'). However, could more explicitly contrast with 'search' or 'summarize' siblings.

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?

Provides prerequisite ('Requires WEBCLAW_API_KEY') and implies usage context through 'deep' and async behavior, but lacks explicit when-to-use guidance versus alternatives like 'search' for quick lookups or 'scrape' for specific extraction.

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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