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'.
82
72%
Does it follow best practices?
Impact
100%
1.72xAverage 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 DAB config
Memory dependency
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Database resource type
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database_name value
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CAN_CONNECT_AND_CREATE permission
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LAKEBASE_INSTANCE_NAME wiring
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value_from matches resource name
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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 config
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Profile in CLI commands
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Autoscaling Lakebase DAB config
Postgres resource type
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Branch full path format
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Database full path format
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Internal database ID used
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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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.env autoscaling vars
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EMBEDDING_ENDPOINT and EMBEDDING_DIMS
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Embedding dims value
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Profile in CLI commands
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SP permissions grant workflow
Profile flag on all commands
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Deploy before grant
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Get SP client ID command
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Uses service_principal_client_id
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grant_lakebase_permissions.py invocation
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--memory-type flag
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bundle run after grant
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LakebaseClient create_role first
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LakebaseClient identifier type
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Grant step marked as critical
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Memory dependency included
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100%
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