Stockroom User Guide¶
Stockroom keeps a local warehouse of your Cursor and Claude Code history so you (or an agent) can search past work later. You install and initialize once; after that the loop is mostly ask → answer, with a quiet nightly job keeping the warehouse fresh.
This page is a light mental model only — not the full Architecture tour.
Just want to get it working? Head over to the Quickstart page.
What you do¶
Install Once¶
Install the plugin from the marketplace and run the sr-initialize skill.
That does a one-time dependency sync, selects the correct PyTorch for your machine, does the initial load of the warehouse and offers to schedule a nightly warehouse refresh.
sequenceDiagram
actor You
participant Harness as Cursor / Claude
participant Init as sr-initialize
participant Eng as stockroom CLI
participant WH as warehouse.duckdb
You->>Harness: Install plugin
You->>Harness: /sr-initialize
Harness->>Init: orchestrate
Init-->Eng: install PyTorch
Init->>Eng: install stockroom CLI
Init->>Eng: optional nightly schedule
Init->>Eng: ingest --full && embed
Eng->>WH: write sessions / messages / embeddings
Note over You,WH: Setup done — warehouse searchable
Use It¶
Ask your agents to /sr-search ... for things, or notice them searching on their own.
Outside your harnesses, you can use the stockroom query <SQL> and stockroom semantic <text> CLI commands to dig into the warehouse w/out spending any tokens.
The Dashboard will be there for a visual summary of your work, too.
sequenceDiagram
actor You
participant Harness as Cursor / Claude
participant Eng as stockroom CLI
participant WH as warehouse.duckdb
alt Agent skills
You->>Harness: /sr-search "..."
Harness->>Eng: query and/or semantic
Eng->>WH: read
WH-->>You: hits / answer
else CLI directly
You->>Eng: stockroom query "<SQL>" <br> stockroom semantic "<text>"
Eng->>WH: read
WH-->>You: rows / hits
else Dashboard
You->>Harness: /sr-dashboard
Harness->>Eng: stockroom dashboard
Eng-->>You: http://localhost:58008/
end
Stay Fresh¶
If you opted into a nightly warehouse refresh, it will ingest new conversations & generate embeddings for them each night.
You can also use the stockroom ingest and stockroom embed CLI commands to catch up manually.
sequenceDiagram
actor You
participant Night as Nightly schedule
participant Eng as stockroom CLI
participant WH as warehouse.duckdb
loop Every night
Night->>Eng: ingest && embed
Eng->>WH: catch up
end
opt Results feel stale
You->>Eng: ingest then embed
Eng->>WH: catch up now
end
Where Next?¶
- Get it working with Quickstart
- Learn more about the ETL process on Load the Warehouse
- Recover history from before your harness kept transcripts with Backfill Legacy History
- Troubleshoot PyTorch at Troubleshooting > Torch