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From backup-planner
Recommend the best-fit backup strategy for the project given its data inventory and the user's available infrastructure. Produces a ranked options brief with trade-offs. Use after architecture and inventory are mapped.
How this skill is triggered — by the user, by Claude, or both
Slash command
/backup-planner:evaluate-backup-optionsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Synthesize the data inventory and the available infrastructure into 2–3 concrete strategy options, with a clear recommendation.
Synthesize the data inventory and the available infrastructure into 2–3 concrete strategy options, with a clear recommendation.
backup-plan/01-architecture.mdbackup-plan/02-data-inventory.mdreference_backup_* memory files (see save-backup-infra)If any are missing, run the corresponding upstream skill first.
For each candidate strategy, score against:
pg_dump / pg_dumpall for logical, pg_basebackup + WAL for PITR, or managed provider snapshotsmysqldump, mariabackup, or managed snapshotsVACUUM INTO or file copy with WAL checkpointmongodump, or Ops ManagerWrite to backup-plan/03-options.md:
# Backup Strategy Options
## Option A — <name>
- Tooling: ...
- Destinations: ...
- RPO/RTO delivered: ...
- 3-2-1 status: ...
- Monthly cost estimate: ...
- Pros / Cons
## Option B — ...
## Recommendation
<which option, why, what open questions remain>
End with an explicit ask to the user to approve one option before moving to document-backup-strategy.
npx claudepluginhub danielrosehill/claude-code-plugins --plugin backup-plannerSearches MemPalace before answering questions about past work, people, projects, or prior decisions. Returns verbatim stored content instead of guessing from model memory.
Guides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Implements vector databases with Pinecone, Weaviate, Qdrant, Milvus, pgvector for semantic search, RAG, recommendations, and similarity systems. Optimizes embeddings, indexing, and hybrid search.