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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'.

79

24.75x
Quality

70%

Does it follow best practices?

Impact

99%

24.75x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

57%Weight 40%Scale 1-5

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

The content is highly actionable with concrete commands and YAML, and is well-sectioned, but suffers from a duplicate Step 5 header defect, missing validation checkpoints for destructive operations, and no progressive file structure for its sizable inline reference material.

Suggestions

Fix the duplicate Step 5 headers: remove or fill the empty "## Step 5: Initialize Tables" header and renumber so the deploy step aligns with the workflow diagram.

Add an explicit validation checkpoint after granting SP permissions (e.g., verify the grant succeeded or check expected roles/tables) before proceeding to run the app, turning the CRITICAL warning into a validate-fix-retry loop.

Move the full databricks.yml example and the LakebaseClient API reference into separate reference files linked from the body to improve progressive disclosure and reduce inline length.

DimensionReasoningScore

Conciseness

The body is mostly concrete commands and YAML, but the Use Cases table and Overview list redundantly re-explain short-term/long-term memory, and the inline LakebaseClient API reference plus full databricks.yml example add length that could be trimmed.

3 / 5

Actionability

Provides copy-paste-ready CLI commands with --profile, complete YAML snippets, and exact grant-script invocations with flags; minor gaps are placeholder values (<profile>, <app-name>) and a referenced external YAML file not present in the bundle.

4 / 5

Workflow Clarity

A 7-step sequence with a diagram is present, but there are duplicate "Step 5" headers (an empty "Initialize Tables" followed by "Deploy") and no explicit validate-then-proceed checkpoints for the destructive/batch deploy and grant-permissions steps, which caps this dimension at 3 per the rubric.

3 / 5

Progressive Disclosure

The skill is a single ~340-line SKILL.md with no bundle files (references/scripts/assets are absent), and large reference material (full databricks.yml example, LakebaseClient API section) is inlined rather than split into separate files, so structure exists but content that should be separate is inline.

3 / 5

Total

13

/

20

Passed

Description

82%Weight 40%Scale 1-5

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

The description is well-structured with explicit third-person voice, a clear what/when split, and concrete trigger phrases including natural user terms and specific error messages. Its only weak spot is capability specificity, which lists a single high-level action rather than multiple concrete operations.

DimensionReasoningScore

Specificity

"Configure Lakebase for agent memory storage" names the domain and one concrete action (configure), but does not enumerate multiple specific capabilities, matching the anchor for naming the domain with 1-2 concrete actions.

3 / 5

Completeness

Explicitly states what it does ("Configure Lakebase for agent memory storage") and when to use it via a numbered "Use when:" list with concrete trigger phrases, matching the anchor for clearly answering both what and when.

5 / 5

Trigger Term Quality

Includes natural phrases users would say ("lakebase", "memory setup", "add memory") plus concrete error strings ("Failed to connect to Lakebase", "Permission errors on checkpoint/store tables"), giving good keyword coverage just short of fully comprehensive.

4 / 5

Distinctiveness Conflict Risk

"Lakebase" is a distinct niche with specific trigger terms ("lakebase", "memory setup", error strings) unlikely to fire for unrelated skills, indicating minimal conflict risk.

5 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 3 missing

Warning

Total

15

/

16

Passed

Repository
databricks/app-templates
Reviewed

Table of Contents

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