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'.
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.mdQuality
Discovery
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 coverage and explicit 'Use when' guidance. It excels at distinctiveness due to the specific technology name and error messages. The main weakness is that the 'what' portion could be more specific about the concrete actions performed during configuration.
Suggestions
Expand the capability description to list specific actions, e.g., 'Configure Lakebase connection strings, set up checkpoint/store tables, and grant permissions for agent memory storage.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Lakebase, agent memory storage) and mentions some actions like configuring and troubleshooting specific errors, but doesn't list multiple concrete configuration steps or actions beyond 'configure'. | 2 / 3 |
Completeness | Clearly answers both 'what' (configure Lakebase for agent memory storage) and 'when' with an explicit 'Use when' clause covering four distinct trigger scenarios including feature requests, error conditions, and keyword triggers. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'lakebase', 'memory setup', 'add memory', plus specific error messages like 'Failed to connect to Lakebase' and 'Permission errors on checkpoint/store tables' that users would encounter and mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with specific technology 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 |
Implementation
55%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill is highly actionable with excellent workflow clarity, providing concrete commands, complete configurations, and a well-sequenced 7-step process with critical validation warnings. However, it is severely bloated — the complete YAML examples duplicate earlier step-by-step content, and reference material (API docs, SP identifiers, troubleshooting) should be in separate files. The result is a token-expensive skill that buries its core value in repetitive detail.
Suggestions
Move the two complete databricks.yml examples to a separate `examples/` directory and reference them, since they largely duplicate the step-by-step YAML snippets already shown in Steps 3-4.
Extract the LakebaseClient API reference and Service Principal Identifiers sections into a separate REFERENCE.md file, keeping only a one-line pointer in the main skill.
Consolidate the 'Use Cases' table and 'Overview' section — they cover overlapping information about short-term and long-term memory. Pick one format and remove the other.
Move the troubleshooting table to a separate TROUBLESHOOTING.md file and reference it with a single line, reducing the main skill's token footprint significantly.
| Dimension | Reasoning | Score |
|---|---|---|
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 Steps 3-4). The Use Cases table and Overview section overlap significantly. The LakebaseClient API reference section and SP identifiers section add substantial length that could be in a separate reference file. | 1 / 3 |
Actionability | The skill provides fully executable commands, complete YAML configurations, specific CLI commands with profile flags, and concrete code examples for the LakebaseClient API. Every step has copy-paste ready content with specific parameter values and clear placeholders. | 3 / 3 |
Workflow Clarity | The 7-step workflow is clearly sequenced with an ASCII diagram overview. Step 6 includes a critical WARNING about permissions with explicit error messages that would occur if skipped. The troubleshooting table maps specific error messages to causes and solutions, providing effective feedback loops for error recovery. | 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 could all be in separate referenced files. References to external files exist (e.g., `.claude/skills/add-tools/examples/lakebase.yaml`, other skills) but the content that should be offloaded remains inline, making the file overwhelming. | 1 / 3 |
Total | 8 / 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- databricks/app-templates
- Commit
dfeb4ac
- Reviewed
Table of Contents
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