Configure Lakebase for agent memory storage. Use when: (1) Adding memory capabilities to the agent, (2) 'Failed to connect to Lakebase' errors, (3) Permission errors on checkpoint/store tables, (4) User says 'lakebase', 'memory setup', or 'add memory'.
80
72%
Does it follow best practices?
Impact
92%
3.40xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./agent-langgraph-advanced/.claude/skills/lakebase-setup/SKILL.mdProvisioned Lakebase config for LangGraph agent
Memory extra dependency
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Provisioned resource type
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Correct instance name field
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database_name field
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CAN_CONNECT_AND_CREATE permission
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LAKEBASE_INSTANCE_NAME via value_from
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EMBEDDING_ENDPOINT in databricks.yml
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EMBEDDING_DIMS in databricks.yml
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.env LAKEBASE_INSTANCE_NAME
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.env EMBEDDING settings
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CLI profile included
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bundle run after deploy
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Autoscaling Lakebase config for OpenAI agent
Autoscaling resource type
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Branch field full path
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Database field full path with ID
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CAN_CONNECT_AND_CREATE permission
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LAKEBASE_AUTOSCALING_PROJECT env var
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LAKEBASE_AUTOSCALING_BRANCH env var
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EMBEDDING_ENDPOINT in databricks.yml
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EMBEDDING_DIMS in databricks.yml
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.env autoscaling vars
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.env EMBEDDING settings
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Discovery commands use postgres API
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Discovery commands include profile
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SP permission grant workflow after deploy
Gets SP client_id via CLI
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Runs grant script
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Correct memory-type flag
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Instance name in grant script
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Profile on grant script
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Bundle run command
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Profile on bundle run
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SP client_id used in grant
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No deploy command
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