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databar-ai

Databar MCP Server

Official
by databar-ai

run_bulk_waterfall

Run batch waterfall enrichment on multiple records by specifying a waterfall identifier and parameter list. Optionally set providers and email verifier.

Instructions

Execute a waterfall enrichment on multiple inputs at once. Subject to spending limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waterfall_identifierYesThe identifier of the waterfall to run
params_listYesArray of parameter objects, one per record
provider_idsNoOptional: Specific provider IDs to use
email_verifierNoOptional: Email verifier enrichment ID
Behavior2/5

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

No annotations provided, so the description must disclose behavior. It only mentions spending limits, but does not state side effects (e.g., mutating data, costs, idempotency). Lacks clarity on boundaries or required permissions.

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 concise sentences with no filler. Every word adds value.

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

Completeness2/5

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

With 4 parameters, no output schema, and no annotations, the description is too minimal. It lacks explanation of return values, error handling, or how spending limits affect execution.

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%, so the schema already documents parameters. The description adds no extra meaning for any parameter, making it baseline value.

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?

The description clearly states it executes a waterfall enrichment on multiple inputs at once. It distinguishes from run_waterfall (single input) but not clearly from run_bulk_enrichment or other bulk tools.

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?

Only mentions spending limits as a constraint. No guidance on when to use this tool versus alternatives like run_bulk_enrichment or run_waterfall.

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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