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aiox-data-engineer

Activate the AIOX Database Architect & Operations Engineer agent (Dara). Use for database design, schema architecture, Supabase configuration, RLS policies, migrations, query optimization, data modeling, operations, and monitoring Trigger when user asks to data-engineer, or says 'activate data-engineer', 'switch to data-engineer', '@data-engineer'.

54

Quality

61%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./.kimi/skills/aiox-data-engineer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

38%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 skill delivers a concrete activation protocol and useful operational commands, but it is bloated by a triple-repeated command list and an inlined persona YAML whose external dependency references point to files not included in the bundle. Consolidating the command definitions, moving the agent YAML to a referenced file, and fixing the stale command names in the workflow would materially raise the score.

Suggestions

Deduplicate the command definitions: keep a single canonical command list and have the Star Commands table, YAML block, and Quick Commands section all derive from it rather than restating it three times.

Move the full agent YAML definition into a referenced bundle file and replace the inline block with a one-level-deep pointer, which would also surface the external dependency references clearly instead of burying them in YAML.

Fix the Typical Workflow to use current command names (replace *rls-audit with *security-audit and *explain with *analyze-performance) and add explicit validation checkpoints (e.g. dry-run before apply-migration, security-audit before deploy) between steps since migrations are destructive operations.

DimensionReasoningScore

Conciseness

At 569 lines it is noticeably verbose: the command list is repeated three times (Star Commands table, YAML commands block, Quick Commands section) and the persona YAML carries padding (zodiac '♊ Gemini', archetype, Spanish vocabulary list) that does not advance the task.

2 / 5

Actionability

The activation protocol and CodeRabbit CLI invocations are concrete and executable, but the core database operations are delegated to dependency files (e.g. db-apply-migration.md, security-audit.md) that are not present in the bundle, leaving key execution details missing.

3 / 5

Workflow Clarity

A Typical Workflow is sequenced (Design → Bootstrap → Migrate → Secure → Optimize → Test) and the activation steps are ordered, but validation checkpoints are only implicit and the workflow references stale command names (*rls-audit, *explain) that no longer exist in the command table.

3 / 5

Progressive Disclosure

No bundle files exist, yet the body inlines a ~400-line full agent YAML definition that clearly belongs in a separate file, and references to external dependency files are buried inside that YAML rather than clearly signaled from navigable section headers.

2 / 5

Total

10

/

20

Passed

Description

83%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 well-constructed description that clearly states the agent's purpose and provides explicit, natural-language activation triggers. Minor tightening of capability phrasing into verbs and adding a few more user-natural trigger variations would push it to the top anchor.

DimensionReasoningScore

Specificity

Lists several specific capability areas (database design, schema architecture, Supabase configuration, RLS policies, migrations, query optimization, data modeling, operations, monitoring) alongside the concrete 'Activate' action, though they are domain nouns rather than explicit action verbs.

4 / 5

Completeness

Explicitly answers both what ('Activate the AIOX Database Architect & Operations Engineer agent (Dara)... Use for...') and when ('Trigger when user asks to data-engineer, or says...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes good natural trigger phrases users would say ('activate data-engineer', 'switch to data-engineer', '@data-engineer', 'data-engineer') plus domain keywords, though some natural phrasings like 'design my database schema' or 'help with RLS' are not enumerated.

4 / 5

Distinctiveness Conflict Risk

Has a clear database/data-engineer niche with specific named triggers, but the broad database domain creates minor overlap risk with closely related agent skills like @architect and @dev (which the skill itself acknowledges).

4 / 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

skill_md_line_count

SKILL.md is long (570 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
SynkraAI/aiox-core
Reviewed

Table of Contents

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