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Send Offline Conversion Event

meta_send_offline_event

Send offline conversion events such as in-store purchases or phone orders to Meta offline event sets using hashed customer data.

Instructions

Sends an offline conversion event to a Meta offline event set.

Used for tracking in-store purchases, phone orders, or other offline conversions.

Args:

  • event_set_id (string): Offline event set ID (from meta_list_offline_event_sets)

  • event_name (string): Event name (e.g., "Purchase", "Lead")

  • event_time (number): Unix timestamp of the conversion

  • user_data (object): Customer match data — at least one of: email, phone, fn (first name), ln (last name), ct (city), st (state), zip, country, external_id. All PII must be SHA256 hashed.

  • custom_data (object, optional): { currency, value, content_name, order_id }

  • upload_tag (string, optional): Tag for grouping uploads

Returns: Number of events received.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_set_idYesOffline event set ID
event_nameYesEvent name (e.g., 'Purchase')
event_timeYesUnix timestamp
user_dataYesCustomer match data (hashed PII)
custom_dataNo
upload_tagNoTag for grouping uploads
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior5/5

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

Discloses that PII must be SHA256 hashed, describes return value (number of events received), and aligns with annotations (readOnlyHint=false indicates writes, no contradiction). Provides behavioral context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded purpose with clear parameter list. Brief but covers all necessary details. Could combine some sentences but overall efficient.

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

Completeness5/5

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

Comprehensive for a complex tool with nested objects and no output schema. Covers usage, parameter details, hashing requirement, and return value. Leaves no major gaps given sibling context.

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

Parameters5/5

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

Adds critical meaning beyond schema: specifies required fields in user_data (email, phone, etc.), notes hashing requirement, and enumerates custom_data fields. Schema coverage is high (86%), but description still enhances usability.

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?

Clearly states the verb 'sends', resource 'offline conversion event to a Meta offline event set', and provides usage examples (in-store purchases, phone orders). Distinguishes from siblings like meta_send_conversion_event for online events.

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?

Explicitly states when to use ('for tracking in-store purchases, phone orders, or other offline conversions') and implies differentiation from online event tools. Does not explicitly exclude alternatives, but context is clear.

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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