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lakebase-setup

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

3.40x
Quality

72%

Does it follow best practices?

Impact

92%

3.40x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./agent-langgraph-advanced/.claude/skills/lakebase-setup/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

55%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is highly actionable with excellent workflow clarity and a well-structured multi-step process with critical validation checkpoints. However, it is severely bloated — the complete YAML examples duplicate earlier step-by-step content, and reference material like the LakebaseClient API and SP identifiers should be in separate files. The skill would benefit enormously from aggressive content splitting and deduplication.

Suggestions

Move the complete databricks.yml examples to a separate file (e.g., `examples/lakebase-complete.yaml`) and reference it, since the step-by-step instructions already show the relevant YAML snippets.

Extract the LakebaseClient API reference and Service Principal Identifiers sections into a separate reference file (e.g., `LAKEBASE_REFERENCE.md`) — these are lookup material, not setup instructions.

Remove the 'Use Cases' section or reduce it to a single sentence — Claude doesn't need a detailed explanation of what memory types exist to configure Lakebase.

Consolidate the Overview section with the Use Cases table — they overlap significantly in describing short-term vs long-term memory.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~350+ lines. It includes massive complete YAML examples that are largely duplicative (the full databricks.yml examples repeat most of what was already shown in Step 3), explains concepts like what Lakebase is used for in a detailed table, and provides extensive reference material (LakebaseClient API, SP identifiers) that could be in separate files. There is significant redundancy between the step-by-step instructions and the complete examples section.

1 / 3

Actionability

The skill provides fully executable commands, complete YAML configurations, concrete bash commands with proper profile flags, and specific Python code for the LakebaseClient API. Every step has copy-paste ready content with placeholders clearly marked.

3 / 3

Workflow Clarity

The 7-step workflow is clearly sequenced with an ASCII diagram overview, explicit validation points (Step 6 is marked CRITICAL with a WARNING), error recovery guidance in troubleshooting, and clear dependencies between steps (deploy before granting permissions, run after deploy). The feedback loop for permission errors is well-documented.

3 / 3

Progressive Disclosure

The skill is a monolithic wall of text with everything inline. The complete YAML examples, LakebaseClient API reference, SP identifier details, and troubleshooting table should all be in separate referenced files. References to external files exist (e.g., `.claude/skills/add-tools/examples/lakebase.yaml`) but the content is still duplicated inline. The 'Next Steps' section references other skills but the body itself fails to offload any content.

1 / 3

Total

8

/

12

Passed

Description

89%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a well-structured skill description with strong trigger terms and explicit 'Use when' guidance covering both proactive setup and reactive troubleshooting scenarios. The main weakness is that the 'what' portion is somewhat thin—it says 'configure' but doesn't elaborate on specific configuration actions (e.g., creating tables, setting permissions, connecting endpoints). Overall it performs well for skill selection purposes.

Suggestions

Expand the capability description to list specific concrete actions, e.g., 'Configure Lakebase for agent memory storage: create checkpoint/store tables, set permissions, establish connection endpoints.'

DimensionReasoningScore

Specificity

Names the domain (Lakebase, agent memory storage) and mentions some actions like configuring and troubleshooting errors, but doesn't list multiple concrete actions beyond 'configure'. The error scenarios add some specificity but are more about triggers than capabilities.

2 / 3

Completeness

Clearly answers both 'what' (configure Lakebase for agent memory storage) and 'when' with an explicit 'Use when:' clause listing four distinct trigger scenarios including user phrases and error conditions.

3 / 3

Trigger Term Quality

Includes natural keywords users would say: 'lakebase', 'memory setup', 'add memory', plus error messages like 'Failed to connect to Lakebase' and 'Permission errors on checkpoint/store tables' that users would encounter and paste directly.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with specific product name 'Lakebase', specific error messages, and niche domain of agent memory storage configuration. Very unlikely to conflict with other skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
databricks/app-templates
Reviewed

Table of Contents

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