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DatalisHQ

ZuckerBot

by DatalisHQ

zuckerbot_refresh_audience

Rebuild seed audiences from latest CAPI events and sync lookalike audience status from Meta. Use after new conversion events arrive.

Instructions

Rebuild a stored audience from fresh data. For seed audiences: re-hashes the latest CAPI events for the source CRM stage. For lookalike audiences: syncs the current size and delivery status from Meta after the seed refreshes. Use this when CAPI has received new events since the audience was last built.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audience_idYesStored audience row ID
Behavior4/5

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

With no annotations, the description discloses key behavioral traits: for seed audiences it re-hashes latest CAPI events, for lookalikes it syncs size and delivery status. It does not mention permissions or error handling, but the core behavior is well explained.

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 efficiently convey core function, subtype behaviors, and usage guidance. No wasted words, well-structured.

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 the simple schema and lack of output schema, the description covers the essential aspects: behavior for both audience types and when to use. It omits return value details but is otherwise complete.

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 one parameter (audience_id) described as 'Stored audience row ID.' The description adds no additional semantic beyond what the schema provides, so baseline score is appropriate.

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 it rebuilds a stored audience from fresh data, with specific behaviors for seed and lookalike audiences. It distinguishes from sibling tools like create_seed_audience, delete_audience, and get_audience_status.

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 advises 'Use this when CAPI has received new events since the audience was last built,' providing a clear condition for use. It does not explicitly state when not to use it but implies that creation of new audiences is handled by other 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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