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Official agent skill

Data Manager API Event Ingestion

by google in google/skills

Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries.

OfficialApache-2.0Auto-check passedMarketing & SEO

Install Data Manager API Event Ingestion

skills CLI
$ npx skills add google/skills --skill data-manager-api-event-ingestion -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google/skills data-manager-api-event-ingestion --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/data-manager-api-event-ingestion .claude/skills/data-manager-api-event-ingestion && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
data-manager-api-event-ingestion
GitHub stars
21k
Token cost
~2.8k tokens
SKILL.md length
948 words
Files
1
Skills in repo
145
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries.

  • Works in 4 steps: Identify Use Case & Read Documentation → Retrieve Code Sample → Retrieve Migration Guides → …
  • The user wants to upload offline conversions
  • SKILL.md covers Implementation Workflow, Formatting, Critical Gotchas and Error Handling & Troubleshooting, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Data Manager API Event Ingestion is an agent skill from google/skills, published by the product's own GitHub organization. Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Paid advertising. It works with Google Analytics and Google Ads. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.

When your agent uses it

  • The user wants to upload offline conversions
  • Enhanced conversions for leads
  • Click conversions
  • Google Analytics web

Example prompts

  • “Use the data-manager-api-event-ingestion skill to guide developers through implementing event and conversion ingestion to Google products using the…”
  • “/data-manager-api-event-ingestion”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Identify Use Case & Read Documentation
  2. Retrieve Code Sample
  3. Retrieve Migration Guides
  4. Implementation

What it can do on your machine

Read from SKILL.md and the folder at commit 8a1ac05. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • developers.google.com
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Data Manager API Event Ingestion loads about 2.8k tokens when it runs. Until then it costs about 133 tokens; SKILL.md has 948 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~133
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from google/skills at commit 8a1ac05, republished under its Apache-2.0 licence (© google). 948 words, ~2,820 tokens.

Download SKILL.mdSave it as .claude/skills/data-manager-api-event-ingestion/SKILL.md (or your agent's skills folder).
name
data-manager-api-event-ingestion
description
Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).
metadata.version
1.2.0
metadata.category
GoogleAds

Data Manager API Event Ingestion

Implementation Workflow

Prerequisites
  • Authentication & Library Installation: If you need to set up access to the Data Manager API or install the client and utility libraries, refer to the data-manager-api-setup skill.
Step 1: Identify Use Case & Read Documentation
  • Determine Destination Account Type: [CRITICAL] If it can't be determined from the user's context, consider clarifying which destination events are being ingested to before generating any code. This maps to the account_type field of the operating_account in the Destination, and also determines valid event identifiers and requirements.
  • Identify User Intent:
    • Implementing ingestion code: Follow the relevant implementation guide for the destination and use case in the Implementation guide column below. This is critical to ensure field requirements are met and destinations are correctly configured.
    • Checking request status or inspecting errors: Refer to the Error Handling & Troubleshooting section below.
    • Migrating from another Google API: Refer to Step 3: Retrieve Migration Guides below to extract the full contents of the relevant field mapping guide.
Destination (operating_account.account_type)Use caseImplementation guide
Google Ads (GOOGLE_ADS)Offline conversions, enhanced conversions for leadsSend events
Google Ads (GOOGLE_ADS)Multi-source conversions supplementing the Google tagSend events
Google Ads (GOOGLE_ADS)Store sales conversionsSend events
Google Analytics (GOOGLE_ANALYTICS_PROPERTY)Recommended and custom GA4 eventsSend events
Google Analytics (GOOGLE_ANALYTICS_PROPERTY)Multi-source events with a transaction IDSend events
Floodlight (FLOODLIGHT_CONFIG)Floodlight offline conversionsSend events
Floodlight (FLOODLIGHT_CONFIG)Multi-source conversions supplementing the Google or Floodlight tagSend events

If the request doesn't match any row, fetch the Events overview to find the right guide rather than guessing.

Step 2: Retrieve Code Sample

[!IMPORTANT] If writing or updating an ingestion script, ALWAYS retrieve the relevant code sample to use as a reference:

LanguageSample
Pythoningest_events.py
JavaIngestEvents.java
PHPingest_events.php
Nodeingest_events.ts
.NETIngestEvents.cs
Step 3: Retrieve Migration Guides

[!IMPORTANT] If refactoring code to upgrade from another Google API, ALWAYS extract the full contents of the relevant field mapping guide.

Google Ads
Google Analytics
Floodlight
Step 4: Implementation

Implement the ingestion logic using the following checkpoints:

  • Initialize Client: Instantiate the Data Manager client (IngestionServiceClient).
  • Define Destinations: Build the Destination object using the product_destination_id and the appropriate account configurations: operating_account (target account receiving data), login_account (if authenticating using a manager account or a data partner account), and linked_account (if you're a data partner accessing the account via a partner link to a manager account). STRONGLY RECOMMENDED: Refer to the Configure destinations and headers guide for more details on configuring destinations.
  • Prepare Event Data: Use the utility library helpers to format and normalize user identifiers correctly.
  • Construct Payload: Build the request payload (IngestEventsRequest) containing the destinations, event records, and consent permissions.
  • Support Validation: Support sending the validate_only boolean option on the IngestEventsRequest to allow developers to validate schemas without actually uploading data.
  • Send Request: Execute ingest_events and record the returned request_id for later diagnostics.
  • Check for Ingestion Warnings: If any non-required field had a validation failure, the response from ingest_events will also include field_warnings, a list of FieldWarning objects detailing the issues.
  • Retrieve Request Status: Check the status of the ingestion request using diagnostics. Since request processing is asynchronous, a successful ingestion response (HTTP 200 OK returning a request_id) only indicates the payload was received. To check if the records actually succeeded, partially succeeded, or failed to process, query the client.retrieve_request_status endpoint using the request_id. Skipping this step is a common user mistake.
Show full SKILL.md (314 more words)Show less

Formatting

  • Fetch the Format user data guide and use that as the source of truth for formatting and normalization rules.

  • Use the utility library to format, hash, and encrypt user data (emails, phone numbers, addresses).

    Python Example:

    python
    from google.ads.datamanager_util import Formatter
from google.ads.datamanager_util.format import Encoding

formatter: Formatter = Formatter()

processed_email: str = formatter.process_email_address(
    email, Encoding.HEX
)

Critical Gotchas

  • Format product_destination_id as a numeric string. It is NOT a resource name path.
  • Format event_timestamp strictly in RFC 3339 format. Use the SDK's typed timestamp object instead of a raw string where available.
  • Nest click identifiers (gclid, gbraid, wbraid) inside the ad_identifiers block, not directly on the base event payload.
  • The enum values for ConsentStatus are CONSENT_GRANTED and CONSENT_DENIED. Do not use the values GRANTED and DENIED.
  • Note that consent can be set globally on the IngestEventsRequest or on individual Events.
  • Verify that UserIdentifier uses email_address and phone_number. Do not use the Google Ads API fields hashed_email and hashed_phone_number.
  • Ensure the currency field on the event is named currency, not currency_code.
  • Do not call the diagnostics endpoint (retrieve_request_status) if validate_only is set to true.

Error Handling & Troubleshooting

Inspecting Error Payloads & Ingestion Warnings

[!IMPORTANT] Refer to Understand API Errors for a detailed guide on how to understand the structure of errors and warnings returned by the API.

Retrieving Request Status (Diagnostics)

Periodically poll for status using exponential backoff, starting at least 30 minutes after sending the IngestEventsRequest.

  1. Call client.retrieve_request_status using RetrieveRequestStatusRequest(request_id=...).
  2. Loop through request_status_per_destination in the response to inspect each target's request_status.
  3. If processing is complete and request_status is SUCCESS, PARTIAL_SUCCESS, or FAILED, inspect diagnostic values:
    • Event Record Counts: Check events_ingestion_status.record_count (includes both success and failure).
    • Error Details: If status is FAILED or PARTIAL_SUCCESS, inspect each error's reason and record_count under error_info.error_counts.
    • Warning Details: Inspect each warning's reason and record_count under warning_info.warning_counts (even if the destination status is SUCCESS).

API Reference

© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ads/data-manager-api-event-ingestion of google/skills.

Open the folder on GitHubat commit 8a1ac05

Compare with similar skills

Data Manager API Event Ingestion next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Data Manager API Event Ingestion compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Data Manager API Event Ingestion this skillgoogle/skills21k—~2.8kAutomated safety check: PassApache-2.0
Blog GoogleAgriciDaniel/claude-blog2.3k1 repos~3.3kAutomated safety check: NotesMIT
SEO Googleseranking/seo-skills160—~4.8kAutomated safety check: PassMIT
Google Adsarnabbagxd/Brand-building-skills719—~3.1kAutomated safety check: PassMIT
Ad Conversion Tracking Setupminhnv0807/ai-business-skills608—~3.7kAutomated safety check: PassMIT
Attribution Reportindranilbanerjee/digital-marketing-pro8541 repos~3.3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Data Manager API Event Ingestion

What does Data Manager API Event Ingestion do?

Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Data Manager API Event Ingestion is an agent skill from google/skills, published by the product's own GitHub organization. Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries.

When should I use Data Manager API Event Ingestion?

Data Manager API Event Ingestion fits situations like: the user wants to upload offline conversions; enhanced conversions for leads; click conversions; google Analytics web.

How do I install Data Manager API Event Ingestion in Claude Code?

Run `npx skills add google/skills --skill data-manager-api-event-ingestion -a claude-code`. Or copy the skill folder (skills/ads/data-manager-api-event-ingestion in google/skills) into .claude/skills/data-manager-api-event-ingestion in your project. Claude Code loads it when a task matches its description.

How do I install Data Manager API Event Ingestion in Codex?

Run `npx skills add google/skills --skill data-manager-api-event-ingestion -a codex`. Or copy the skill folder (skills/ads/data-manager-api-event-ingestion in google/skills) into .agents/skills/data-manager-api-event-ingestion in your project. Codex loads it when a task matches its description.

Can I use Data Manager API Event Ingestion in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill data-manager-api-event-ingestion -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-manager-api-event-ingestion, .gemini/skills/data-manager-api-event-ingestion, .github/skills/data-manager-api-event-ingestion and .opencode/skills/data-manager-api-event-ingestion in your project.

What does Data Manager API Event Ingestion need to run?

SKILL.md names no scripts, command-line tools or credentials: Data Manager API Event Ingestion is instructions for the agent only. Our summary lists: Python 3.

Does Data Manager API Event Ingestion access the network?

SKILL.md names 2 domains. As links in the text: developers.google.com and github.com. This is read from the text; nothing was executed.

Is Data Manager API Event Ingestion safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Data Manager API Event Ingestion use?

Data Manager API Event Ingestion is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Data Manager API Event Ingestion use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Data Manager API Event Ingestion?

Skills that share tags, products or a category with Data Manager API Event Ingestion: Blog Google (AgriciDaniel/claude-blog, 2.3k stars), SEO Google (seranking/seo-skills, 160 stars), Google Ads (arnabbagxd/Brand-building-skills, 719 stars) and Ad Conversion Tracking Setup (minhnv0807/ai-business-skills, 608 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Data Manager API Event Ingestion?

google (a GitHub organization, an official publisher) maintains it in google/skills, which has 20,994 GitHub stars. The repository holds 145 skills in this directory. The repository was last updated on October 6, 2026.

Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.