Agent skill · software engineering · jeremylongshore
algolia-data-handling
Design and audit the data lifecycle for records and user events sent to Algolia. Use when minimizing indexed fields, handling deletion requests, or documenting retention and privacy boundaries. Trigger with "Algolia privacy", "delete Algolia user data", or "index data review".
Why this skill is useful
Provides specific commands and workflows for handling PII and compliance with Algolia that the AI wouldn't reliably generate on its own.
What it needs
Requires algolia account access. About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Algolia Data Handling Review Overview This skill maps which data leaves the source system, how it becomes searchable records or events, and how correction and deletion propagate. It does not claim legal compliance; it produces technical evidence for the responsible privacy owner. Prerequisites A named repository, environment, and Algolia application or index in scope The local lockfile and installed client types as implementation authority A safe read-only query or explicitly disposable test target Current first-party documentation for any provider behavior that affects the change Tool Discipline Use Read, Glob, and Grep to inspect local code, configuration names, tests, and dependency versions. Use WebFetch only for current official Algolia documentation. Use Write or Edit only after identifying the target files, constraints, and verification plan. Current Contract Index only fields required for retrieval, ranking, filtering, display, or approved analytics. Treat attributesToRetrieve as response shaping, not as a substitute for excluding sensitive data from records. Keep source-system identity mappings so corrections and deletions are reproducible. Handle record deletion and Insights user-token deletion as separate surfaces with separate evidence. Authentication Use a restricted backend write key for record changes and the documented authorization for user-data deletion. Never include raw secrets or direct personal identifiers in logs or example events. Instructions 1. Inventory record fields, derived attributes, event fields, user tokens, environments, and downstream exports. 2. Classify each field by purpose, sensitivity, source authority, and deletion requirement. 3. Remove unnecessary fields before indexing and test that UI and ranking behavior still work. 4. Implement idempotent correction and deletion paths with request IDs and target indices. 5. Verify absence using bounded lookups and preserve evidence without retaining the deleted value. 6. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/algolia-data-handling