Google AI Data Exporter

Google AI Data Exporter

Quick Reference

Why This Skill Exists

We need this skill because Google AI workflows degrade when auth, schema, and side-effect handling drift when integrations are run ad hoc. This specific skill turns Google AI Data Exporter into a deterministic, auth-checked workflow for exports google ai entities into clean, typed datasets..

Trigger Checklist

• The task explicitly requires Google AI Data Exporter rather than generic brainstorming.
• The provider tenant, workspace, or environment is known before execution begins.
• Credential reuse has been checked before asking for new secrets.
• Success criteria, side effects, and handoff owner are clear.
• If the run mutates provider state, the relevant approval gates are available.

Auth & Access Profile

Inputs (contract)

Outputs (contract)

Step-by-Step Implementation Guide

1. Define the approved entities, fields, and destination contract for Google AI Data Exporter, then constrain the export scope for Google AI before running queries.
2. Validate credential reuse, pagination strategy, and the exact schema version that downstream consumers expect.
3. Implement exports google ai entities into clean, typed datasets. with deterministic extraction, normalization, and integrity metadata for every page or batch.
4. Attach counts, checksums, and schema fingerprints to the export package and block delivery when the contract drifts.
5. Run integration and regression suites that cover unauthorized field expansion, pagination gaps, and partial delivery failures.
6. Publish a delivery-ready export package with scope notes, integrity metadata, and any quarantined records called out explicitly.

Operational Runbook

Preflight

• Validate export scope, filters, and destination expectations before running queries.
• Confirm credentials and verify that the export respects the agreed data minimization policy.

Execution

• Run deterministic queries, preserve pagination/cursor details, and normalize the output schema.
• Attach checksums and row counts to every export package.

Recovery

• Invalidate partial exports and rerun from the last clean page or cursor on failure.
• Stop delivery when the schema drifts outside the declared contract.

Handoff

• Return the export package location, checksums, and schema summary.
• Note any rows filtered, dropped, or quarantined before the package was finalized.

Validation Gates & Test Matrix

• Required validation suites: unit, integration, regression-baseline

Failure Modes & Recovery Playbook

Tool Call Implementation

• Reuse existing credentials first. Check environment variables, secure stores, and active sessions before prompting.
• Start with the smallest authenticated read or validation call that proves identity and scope.
• Preserve request, response, and approval traces in google-ai-export-package so downstream owners do not need to rediscover context.
• If any auth, contract, or approval gate fails, halt execution and attach remediation guidance instead of guessing.

Credential Reuse Policy

• Reuse valid provider credentials by default and prefer tenant-scoped sessions over newly created secrets.
• Prompt for credentials only when they are missing, invalid, expired, or point at the wrong environment.
• For webhook flows, validate the signing secret against a known sample before accepting live traffic.

Guardrails

• quality: Attach counts, checksums, and schema version to every export package. (export-integrity-check)
• compliance: Reject exports that exceed the approved data scope. (data-scope-review)
• reliability: Invalidate partial deliveries instead of handing off incomplete datasets. (partial-delivery-block)

Acceptance Checklist

• Credential preflight and scope validation completed successfully.
• Required validation suites ran and all fail-closed gates passed.
• google-ai-export-package, scorecard, and handoff packet were produced.
• Any mutations, approvals, or rollbacks are reflected in the artifact bundle.

Anti-Patterns

• Do not ask for new credentials before checking reusable auth context.
• Do not skip the read-only or dry-run validation step for mutating work.
• Do not proceed when approval gates, signing secrets, or rollback checkpoints are missing.
• Do not hand off partial or ambiguous provider state as complete.

Handoff Contract

• Produces: google-ai-export-package, execution scorecard, approval trace, and next actions.
• Consumes: export specification, query filters, destination contract.
• Readiness rule: release only after auth, contract, approval, and reliability gates all pass.
• Downstream hint: route to google-ai:data-exporter consumers with approval and credential context attached.

Observability & Continuous Improvement

• SLO: >=99.5% successful runs per 7-day window
• Error budget: <=0.5% critical failures per 7-day window
• Alert triggers:
• credential validation failures exceed baseline
• schema or contract regressions persist for two consecutive runs
• critical posture or rollback events exceed tolerance
• Primary outcome metric: export completeness
• Secondary metrics: schema conformance, delivery latency
• Review cadence: weekly