| name | firestore-operations-manager |
| description | Manage Firebase/Firestore operations including CRUD, queries, batch processing, and index/rule guidance.
Use when you need to create/update/query Firestore documents, run batch writes, troubleshoot missing indexes, or plan migrations.
Trigger with phrases like "firestore operations", "create firestore document", "batch write", "missing index", or "fix firestore query".
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| allowed-tools | Read, Write, Edit, Grep, Glob, Bash(cmd:*) |
| version | 1.0.0 |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| license | MIT |
Firestore Operations Manager
Operate Firestore safely in production: schema-aware CRUD, query/index tuning, batch processing, and guardrails for permissions and cost.
Overview
Use this skill to design Firestore data access patterns and implement changes with the right indexes, security rules, and operational checks (emulator tests, monitoring, and rollback plans).
Prerequisites
- A Firebase project with Firestore enabled (or a local emulator setup)
- A clear collection/document schema (or permission to propose one)
- Credentials for the target environment (service account / ADC) and a plan for secrets
Instructions
- Identify the operation: create/update/delete/query/batch/migration.
- Confirm schema expectations and security rules constraints.
- Implement the change (or propose a patch) using safe patterns:
- prefer batched writes/transactions where consistency matters
- add pagination for large queries
- Check indexes:
- detect required composite indexes and provide
firestore.indexes.json updates
- Validate:
- run emulator tests or a minimal smoke query
- confirm cost/perf implications for the query pattern
Output
- Code changes or snippets for the requested Firestore operation
- Index recommendations (and config updates when needed)
- A validation checklist (emulator commands and production smoke tests)
Error Handling
- Permission denied: identify the rule/role blocking the operation and propose least-privilege changes.
- Missing index: provide the exact composite index needed for the query.
- Hotspot/latency issues: propose sharding, pagination, or query redesign.
Examples
Example: Fix a failing query
- Request: “This query needs a composite index—what do I add?”
- Result: the exact index definition and a safer query pattern if needed.
Example: Batch migration
- Request: “Backfill a new field across 100k docs.”
- Result: batched write strategy, checkpoints, and rollback guidance.
Resources
