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databricks-agent-bricks

Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).

63

Quality

75%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/databricks/claude/skills/databricks-agent-bricks/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

80%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.

Highly actionable, well-structured content with executable commands and a clean reference split, weakened only by the lack of explicit validation checkpoints around its destructive operations.

Suggestions

Add explicit pre-delete validation steps for destructive commands, e.g. 'Run list-… first to confirm the id, then delete' as a numbered feedback loop rather than an inline comment.

Add a readiness feedback loop for the KA flow (poll get-knowledge-assistant until status is ONLINE before proceeding) mirroring the supervisor endpoint-readiness guidance.

DimensionReasoningScore

Conciseness

The body is lean — commands plus terse gotcha comments with no basic-concept padding — but a couple of brief intro lines ('pre-built AI tiles in Databricks that provide conversational interfaces') could be trimmed, matching the 'efficient; minor over-explanation' anchor rather than the fully bare 5.

4 / 5

Actionability

Fully executable, copy-paste-ready `databricks` CLI commands with real flags and JSON payloads cover the common cases (create KA, add source, sync, create supervisor, attach Genie/KA tools, add examples).

5 / 5

Workflow Clarity

Sequences and async-status checks (CREATING→ONLINE, endpoint readiness) are present, but destructive deletes carry only inline 'confirm the id first' warnings with no explicit pre-delete validation feedback loop, so per the guideline workflow clarity is capped at 3.

3 / 5

Progressive Disclosure

The body is a well-organized overview with a Reference table pointing to real, one-level-deep files (references/1-knowledge-assistants.md, references/2-supervisor-agents.md), giving clear navigation and an appropriate content split.

5 / 5

Total

17

/

20

Passed

Description

70%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.

A specific, distinct description that names concrete capabilities in the user's own product vocabulary, but it omits any explicit 'when to use this' trigger guidance, which caps its completeness.

Suggestions

Add a 'Use when...' clause naming concrete triggers, e.g. 'Use when creating Databricks Knowledge Assistants for document Q&A or Supervisor Agents for multi-agent orchestration.'

Include a few natural synonyms/extensions (e.g. 'RAG assistant', 'multi-agent system') to broaden trigger coverage.

DimensionReasoningScore

Specificity

Names the domain (Agent Bricks) and two concrete capabilities with their purposes — 'Knowledge Assistants (KA) for document Q&A' and 'Supervisor Agents for multi-agent orchestration' — matching the 'several specific actions; minor gaps' anchor rather than the 1-2-action anchor below.

4 / 5

Completeness

It clearly states 'what' the skill does but provides no 'when to use it' / 'Use when' trigger clause, so per the judging guideline completeness is capped at 3.

3 / 5

Trigger Term Quality

Uses the actual product vocabulary users would say ('Agent Bricks', 'Knowledge Assistants', 'document Q&A', 'Supervisor Agents', 'multi-agent orchestration'), giving good keyword coverage; falls short of 5 only because no synonyms or extensions are included.

4 / 5

Distinctiveness Conflict Risk

Databricks-specific product names (Agent Bricks, Knowledge Assistants, Supervisor Agents) carve a clear niche with distinct triggers and minimal conflict risk with other skills.

5 / 5

Total

16

/

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
databricks/databricks-agent-skills
Reviewed

Table of Contents

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