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DatalisHQ

ZuckerBot

by DatalisHQ

zuckerbot_set_capi_config

Update Meta Conversions API configuration: map CRM stages to Meta events, enable or disable delivery, and adjust currency, optimisation target, action source, or CRM source. Changes apply immediately.

Instructions

Update the Conversions API configuration for a business. Set stage-to-event mappings (e.g., 'lead' → Meta Lead event), enable/disable delivery, change the CRM source, currency, optimisation target, or action source. Changes take effect immediately for new CAPI events. Use zuckerbot_capi_test to verify the updated config works.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
currencyNoBusiness currency used for CAPI event values, such as USD or AUD
crm_sourceNoCRM source label, such as hubspot
is_enabledNoEnable or disable CAPI delivery for the business
business_idNoOptional business ID override for the authenticated API key
optimise_forNoDownstream optimisation target for autonomous evaluation
action_sourceNoMeta Conversions API action_source. Defaults to website for CRM events
event_mappingNoCRM stage mapping object keyed by source stage. Stage keys are normalised (lower-cased, non-alphanumerics stripped: signup_completed → signupcompleted); inbound webhook source_stage values are normalised identically before matching, and any renamed keys are reported back as normalised_keys in the response
rotate_webhook_secretNoRotate the webhook secret on update. The new secret is returned exactly once in the response; prefer zuckerbot_rotate_webhook_secret for a dedicated rotation
Behavior3/5

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

With no annotations, the description must fully disclose behaviors. It states changes take effect immediately for new CAPI events, which is a key behavioral trait. However, it doesn't mention side effects (e.g., overwriting existing config), authorization needs, or other implications of the rotate_webhook_secret parameter. More detail on what gets destroyed or updated would improve transparency.

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?

The description is three sentences long, front-loaded with the main purpose, then lists capabilities, and ends with behavior and verification suggestion. Every sentence earns its place; there is no redundancy or fluff.

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 tool's complexity (8 parameters, nested objects, many siblings), the description covers the main purpose, configurable items, immediate effect, and testing recommendation. It lacks details on error scenarios, authentication requirements, and full behavioral specification, but overall it is fairly complete for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by providing normalization details for event_mapping keys (lower-cased, non-alphanumerics stripped) and an example mapping ('lead' → Meta Lead event). It also advises preferring a dedicated tool for rotation. This extra context justifies a 4.

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 updates the Conversions API configuration, specifying the verb 'Update' and the resource 'Conversions API configuration'. It lists specific configurable items (stage-to-event mappings, enable/disable, CRM source, currency, etc.), and distinguishes from siblings like get_capi_config (read) and capi_test (test) by mentioning the test tool for verification.

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 advises using zuckerbot_capi_test to verify the updated config, providing a clear post-update action. While it doesn't explicitly state when not to use this tool, it implies it's for modifications and hints at alternatives like zuckerbot_rotate_webhook_secret for dedicated rotation. It lacks prerequisites or context like needing an existing configuration, but the guidance is sufficient.

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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