What does this skill do, and when should you use it?
This skill guides developers through the Data Manager API v1/audienceMembers/ingest endpoint for uploading audience members. It covers Google Ads Customer Match, mobile device ID audiences, and other supported audience use cases. It requires the destination account type to be identified before implementation and points developers to destination-specific documentation and language samples. It also emphasizes normalization, consent handling, validation-only requests, asynchronous status checks, and diagnostics.
It directs the user to identify the destination product and account type, retrieve the relevant Data Manager API documentation, code sample, and migration mapping guide, then initialize IngestionServiceClient and construct Destination and IngestAudienceMembersRequest objects. It instructs developers to normalize, hash, or encrypt identifiers with the utility library, configure consent permissions and validate_only, call ingest_audience_members, and record the request_id. It then uses retrieve_request_status to inspect asynchronous processing results, record counts, match-rate ranges, errors, and warnings.
- A Google Ads integration developer needs to upload processed email, phone, or address identifiers for Customer Match.
- A Display & Video 360 engineer needs to configure the destination and ingest Customer Match audience members.
- A team migrating Customer Match code from another Google API needs field-level migration guidance.
- A developer wants to validate the request schema without uploading data and needs validate_only support.
- An engineer investigating partial or failed uploads needs request-status polling and diagnostic inspection.
How do you install this skill?
- The workflow handles user identity data; confirm lawful authorization, consent status, least-privilege access, and secure logging before sending data.
- The skill depends on external Google documentation, client libraries, and services; verify reachability in the target network and recheck current API and sample compatibility.
- An asynchronous HTTP 200 only confirms request receipt, not record success; retain the request_id and retrieve diagnostics.
- Network access
Data Manager API client librarygoogle.ads.datamanager_util utility library
This skill is included in the google/skills collection. Run the README-supported command: npx skills add google/skills, then select Data Manager API Audience Ingestion during installation. The source does not document a specific installation directory or a separate command for installing only this skill.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/google/skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/ads/data-manager-api-audience-ingestion" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Help me upload Customer Match audience members to Google Ads with the Data Manager API in Python.
Use the directory's SKILL.md as an Agent Skill in a compatible client and provide a request such as: “Help me upload Customer Match audience members to Google Ads with the Data Manager API in Python.” The destination account type must be explicit, such as Google Ads or DV360; otherwise it should be clarified first. When writing or updating an ingestion script, retrieve the official sample for the chosen language before implementing it.
What are this skill's strengths and limitations?
- Covers the workflow from destination identification and formatting through asynchronous diagnostics.
- Calls out concrete pitfalls involving address fields, consent enums, field names, and product_destination_id.
- Links to samples for Python, Java, PHP, Node, and .NET.
- Supports validate_only for pre-upload request validation.
- It does not replace authentication or library setup; those are delegated to data-manager-api-setup.
- Implementation depends on destination-specific documentation and client or utility libraries.
- Asynchronous processing requires waiting at least 30 minutes before beginning status polling.
- The SKILL.md does not provide an automated test suite or specific runtime version requirements.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Google Data Manager API Audience Import Assistant this page ✓ Google · Official | 54 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
| Data Manager API Event Ingestion Guide ✓ Google · Official | 52 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
| Data Manager API Setup Assistant ✓ Google · Official | 48 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
| n8n JavaScript Code Node Guide | 47 · Use with care | ★ 6.4k | 18d ago | MIT |
| Google Ads MCP Setup Guide ✓ Google · Official | 40 · Not recommended | ★ 21k | 12d ago | Apache-2.0 |
Unlike data-manager-api-event-ingestion, this skill handles audience-member uploads rather than event or conversion uploads. Unlike data-manager-api-setup, it focuses on audience-ingestion implementation rather than access setup and library installation.
How did FollowSkills review this skill?
The skill requires confirming the destination account type, describes destination, login, and linked accounts, and calls for normalization, hashing/encryption, consent handling, and validate_only support. It does not specify least-privilege permissions, pre-upload user confirmation, sensitive-data retention or logging policy, revocation or rollback, or dependency and supply-chain controls, so points are deducted.
The workflow gives useful guidance on field pitfalls, asynchronous status checks, exponential backoff, and diagnostics, and correctly excludes diagnostics for validate_only requests. However, it relies on external documentation and samples, with no committed tests, dependency pinning, reproducible key paths, or comprehensive abnormal-input failure feedback. The static cap is applied.
The audience and scenarios are clear, including Customer Match and mobile device IDs, and it explicitly excludes event or conversion uploads while requiring clarification when the destination is unknown. It lacks broader non-fit boundaries, precise trigger rules, and Chinese-language support; core operation depends on Google services that may be difficult to reach from mainland China, so points are deducted.
The skill has version 1.1 metadata, a staged structure, critical gotchas, troubleshooting guidance, and external references. The repository README supplies Apache-2.0 licensing, installation, issue reporting, and active-development context. The skill lacks detailed dependency notes, FAQs, a changelog, explicit maintenance ownership, and a defined update path, so points are deducted.
It covers destination selection, sample retrieval, field mappings, request construction, validation mode, submission, and asynchronous diagnostics, which supports the core implementation. It does not provide a complete directly runnable end-to-end output; key steps depend on external material, and there is no evidence comparing value with manual or alternative approaches. The static cap limits this to 7.
Links to Google developer documentation, API references, and Google-maintained language samples provide auditable primary material. There is no committed test suite, CI execution evidence, or independent corroboration, and no code was executed in this review, so the static cap of 5 applies.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →