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DatalisHQ

ZuckerBot

by DatalisHQ
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

zuckerbot_sync_conversion

Send conversion or bounce feedback for leads to Meta via CAPI, helping the algorithm find better prospects. Use when a lead converts, is uncontactable, or is a bad fit.

Instructions

Send downstream conversion quality feedback to Meta via CAPI. When a ZuckerBot-sourced lead converts (sale, appointment, qualified call) or bounces (uncontactable, bad fit), reporting it here teaches Meta's algorithm to find more (or fewer) people like them — improving lead quality over time. Call this from your CRM when a lead status changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fbcNoOptional pre-formatted fbc cookie, forwarded raw — never hashed
fbpNoOptional _fbp browser cookie, forwarded raw — never hashed. Improves match quality
fbclidNoOptional Facebook click ID; the server builds a well-formed fbc cookie from it
lead_idYesLead ID to report conversion for
qualityYesLead quality: 'good' = converted/contacted, 'bad' = lost/unresponsive
user_dataNoOptional user data to improve match rate
campaign_idYesZuckerBot campaign ID
meta_access_tokenYesUser's Meta access token for CAPI

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.4

TDQS

A4/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses that it teaches Meta's algorithm to improve lead quality. Does not detail authentication needs or side effects, but schema covers required token.

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 sentences, front-loaded with purpose, then usage and benefit. No wasted words.

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?

Provides context on trigger (lead status change) and effect (algorithm improvement). No output schema, but tool likely returns basic status. Adequate for understanding.

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%, baseline 3. Description adds no extra meaning beyond schema; does not explain parameter purpose further.

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?

States it sends conversion quality feedback to Meta via CAPI for ZuckerBot-sourced leads, with specific conversion types. Distinguishes from sibling 'zuckerbot_send_capi_event' by focusing on lead quality feedback.

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?

Clearly specifies when to call: when a lead status changes (converted or bounced). Provides context from CRM. Does not explicitly mention alternatives or exclusions, but context 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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