data-manager-api-audience-ingestion
Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries.
Install / Use
npx skills add google/skills --skill data-manager-api-audience-ingestionInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Customer SupportSupported Platforms
Our assessment of data-manager-api-audience-ingestion
data-manager-api-audience-ingestion scores 90/100 on our quality scale, 34th of 105 Customer Support skills we index (top 33%).
Its SKILL.md is 11 KB long, well organised into 14 sections and no code examples: a thorough specification that gives an agent plenty to work with.
With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 2 days ago, so data-manager-api-audience-ingestion is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
data-manager-api-audience-ingestion compared with similar skills
All 4 of these similar skills score higher than data-manager-api-audience-ingestion; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| data-manager-api-audience-ingestion (this skill)by google | 90 | 20.3k | 2d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.4k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.8k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.7k | today | MCP Server |
| LocalAIby mudler | 100 | 49.3k | today | MCP Server |
Frequently asked questions
- How do I install data-manager-api-audience-ingestion?
- Run
npx skills add google/skills --skill data-manager-api-audience-ingestion. The install tabs above show the steps for each supported agent. - Which AI agents does data-manager-api-audience-ingestion work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is data-manager-api-audience-ingestion safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is data-manager-api-audience-ingestion still maintained?
- The repository was last updated 2 days ago, so data-manager-api-audience-ingestion is actively maintained.
Skill content
View source on GitHubname: data-manager-api-audience-ingestion description: >- Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill). metadata: version: "1.1.0" category: GoogleAds
Data Manager API Audience 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-setupskill. - Audience Creation (if needed): If the user does not have an existing
audience or needs to create a new one, use the
Create an Audience reference. This step
provides the
product_destination_idneeded for the ingestion or removal requests.
Step 1: Identify Use Case & Read Documentation
- Determine Destination Account Type: [CRITICAL] If it's not clear where
the data is being sent (e.g., Google Ads, Display & Video 360, etc.), STOP
and CLARIFY with the user BEFORE generating any code. Do not assume Google
Ads by default. This maps to the
account_typefield of theoperating_accountin theDestination. - Read the implementation guide: Read the relevant guide for your destination and use case. Do this before answering questions or writing code because each destination has unique payload structures, consent rules, and required fields.
| Destination | Audience Type | Accepted Data Types | Upload Guide | Remove All/Replace All Guide |
| :--- | :--- | :--- | :--- | :--- |
| Google Ads | Customer Match | composite_data.user_data (contact info), mobile_data (device IDs), user_id_data (user IDs) | Upload Data | Remove All/Replace All |
| Display & Video 360 (DV360) | Customer Match | composite_data.user_data (contact info), mobile_data (device IDs) | Upload Data | Remove All/Replace All |
Step 2: Retrieve Code Sample
[!IMPORTANT] If writing or updating an ingestion script, ALWAYS retrieve the relevant code sample to use as a reference:
| Language | Sample |
| :--- | :--- |
| Python | ingest_audience_members.py |
| Java | IngestAudienceMembers.java |
| PHP | ingest_audience_members.php |
| Node | ingest_audience_members.ts |
| .NET| IngestAudienceMembers.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 Ads API Customer Match: Google Ads API to Customer Match Migration Field Mappings
Display & Video 360
- Display & Video 360 API Customer Match: Display & Video 360 API to Customer Match Migration Field Mappings
Step 4: Implementation
Implement the ingestion logic using the following checkpoints:
- [ ] Initialize Client: Instantiate the Data Manager client
(
IngestionServiceClient). - [ ] Define Destinations: Build the
Destinationobject using theproduct_destination_idand the appropriate account configurations:operating_account(target account receiving data),login_account(if authenticating using a manager account or a data partner account), andlinked_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. - [ ] Format User Data: If sending an
IngestAudienceMembersRequestorRemoveAudienceMembersRequest, refer to Formatting User Data to properly normalize and hash user identifiers using the utility library. - [ ] Construct Payload: Build the appropriate request payload based on
the operation:
- Add:
IngestAudienceMembersRequest - Remove:
RemoveAudienceMembersRequest - Remove All:
RemoveAllAudienceMembersRequest
- Add:
- [ ] Support Validation: Support sending the
validate_onlyboolean option on the payload to allow developers to validate schemas without actually applying changes. - [ ] Send Request: Execute the appropriate method and record the returned
request_idfor later diagnostics:- Add:
ingest_audience_members - Remove:
remove_audience_members - Remove All:
remove_all_audience_members
- Add:
- [ ] Check for Ingestion Warnings: If any non-required field had a
validation failure, the response from
ingest_audience_memberswill also includefield_warnings, a list ofFieldWarningobjects detailing the issues. - [ ] Retrieve Request Status: Check the status of the ingestion request
using diagnostics. Since request processing is asynchronous, a successful
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, queryclient.retrieve_request_statususing therequest_id. Skipping this step is a common user mistake.
Critical Gotchas
- If sending hashed user identifiers in
user_dataforingest_audience_membersorremove_audience_members, you must set theencodingfield on theIngestAudienceMembersRequesttoHEXorBASE64. - If uploading to a Customer Match audience, the
terms_of_servicefield is required on theIngestAudienceMembersRequestto indicate the user has accepted the policies. - Only set the
addressfield onUserIdentifierif all required fields (postal_code,family_name,given_name,region_code) are present; incompleteaddressfields will cause the API request to fail. product_destination_idmust be a numeric string. It is NOT a resource name.- The enum values for
ConsentStatusareCONSENT_GRANTEDandCONSENT_DENIED. Do not use the valuesGRANTEDandDENIED. - Field names on
UserIdentifierareemail_addressandphone_number. Do not use the Google Ads API field nameshashed_emailandhashed_phone_number. - Do not call the diagnostics endpoint (
retrieve_request_status) ifvalidate_onlyis set totrue.
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 request.
- Call
client.retrieve_request_statususingRetrieveRequestStatusRequest(request_id=...). - Loop through
request_status_per_destinationin the response to inspect each target'srequest_status. - If processing is complete and
request_statusisSUCCESS,PARTIAL_SUCCESS, orFAILED, inspect diagnostic values:- Audience Status: Check the status specific to your request:
- Ingest: Check the data-type-specific status nested under
audience_members_ingestion_status(e.g.,composite_data_ingestion_status). - Remove Individual Members: Check the data-type-specific status
nested under
audience_members_removal_status(e.g.,composite_data_removal_status). - Remove All Members: There are no nested status fields or record counts available to check for this request type.
- Record Count: If applicable (ingest or remove individual
members), check
record_count(nested inside the data-type-specific status object) which includes both success and failure. - Identifier Counts: If applicable (ingest or remove individual
members), check the data-type-specific count field nested inside the
status object (e.g.,
data_type_countsif uploading or removing composite data, ormobile_id_countif uploading or removing mobile IDs). Refer to the Diagnostics Guide for other count fields. - Match Rate Range: For uploads of
user_dataandcomposite_data, checkupload_match_rate_rangenested inside the status object.
- Ingest: Check the data-type-specific status nested under
- Error Details: If status is
FAILEDorPARTIAL_SUCCESS, inspect each error'sreasonandrecord_countundererror_info.error_counts. - Warning Details: Inspect each warning's
reasonandrecord_countunderwarning_info.warning_counts(even if the destination status isSUCCESS).
- Audience Status: Check the status specific to your request:
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
