| name | entityresolution-diagnostics |
| version | 1.0.0 |
| last_updated | 2025-04-12 |
| description | Use this skill to investigate and troubleshoot AWS Entity Resolution problems by analyzing schema mappings, matching workflows, ID mapping workflows, provider services, output configuration, rule-based matching, ML matching, and following structured runbooks. Activate when: schema mapping errors, matching workflow failures, ID mapping issues, provider service configuration, output problems, or the user says something is wrong with Entity Resolution without naming specific symptoms.
|
| compatibility | Requires AWS CLI or SDK access with entityresolution:*, S3, IAM, Glue Data Catalog, and CloudTrail permissions.
|
AWS Entity Resolution Diagnostics
When to use
Any AWS Entity Resolution investigation — schema mapping, matching workflows, ID mapping, provider services, output configuration, or matching algorithm issues.
Investigation workflow
Step 1 — Collect and triage
aws entityresolution list-schema-mappings
aws entityresolution list-matching-workflows
aws entityresolution list-id-mapping-workflows
aws entityresolution list-provider-services
Step 2 — Domain deep dive
aws entityresolution get-schema-mapping --schema-name <name>
aws entityresolution get-matching-workflow --workflow-name <name>
aws entityresolution get-id-mapping-workflow --workflow-name <name>
aws entityresolution list-matching-jobs --workflow-name <name>
Step 3 — Detailed investigation
aws entityresolution get-matching-job --workflow-name <name> --job-id <id>
aws entityresolution get-id-mapping-job --workflow-name <name> --job-id <id>
aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventSource,AttributeValue=entityresolution.amazonaws.com --max-results 20
Read references/guardrails.md before concluding on any Entity Resolution issue.
Tool quick reference
| Tool / API | When to use |
|---|
list-schema-mappings | Enumerate schema mappings |
get-matching-workflow | Check matching workflow config |
list-matching-jobs | Check job execution history |
get-matching-job | Get job details and errors |
get-id-mapping-workflow | Check ID mapping config |
| CloudTrail | Audit configuration changes |
Gotchas: AWS Entity Resolution
- Schema mappings define how input data columns map to Entity Resolution attributes. They reference Glue Data Catalog tables.
- Matching workflows use either rule-based or ML-based matching. Rule-based requires explicit match rules; ML-based uses AWS-trained models.
- ID mapping workflows map identities across datasets using provider services (e.g., LiveRamp, TransUnion).
- Provider services are third-party integrations that require separate subscriptions and configuration.
- Output goes to S3. The IAM role must have write access to the output location.
- Entity Resolution does NOT modify source data. It produces match results as output files.
Anti-hallucination rules
- Always cite specific workflow names, job IDs, or API responses as evidence.
- Entity Resolution is NOT Glue ETL. They are separate services.
- Schema mappings reference Glue Data Catalog, NOT raw S3 files directly.
- ML matching is NOT customizable — it uses AWS pre-trained models.
- Provider services require third-party subscriptions.
- Spend no more than 2 minutes on any single hypothesis. Pivot if inconclusive.
Runbooks
| Category | IDs | Covers |
|---|
| A — Schema | A1–A2 | Schema mapping creation, mapping validation |
| B — Matching | B1–B2 | Matching workflow, rule-based matching |
| C — ML Matching | C1–C2 | ML matching config, match quality |
| D — ID Mapping | D1–D2 | ID mapping workflow, provider services |
| E — Output | E1–E2 | Output configuration, output analysis |
| F — Jobs | F1–F2 | Job execution, job failures |
| Z — Catch-All | Z1 | General troubleshooting |
