aiox-data-engineer

Database Architect & Operations Engineer (Dara). Use for database design, schema architecture, Supabase configuration, RLS policies, migrations, query optimization, data modelin...

Quality

78%

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Securityby

Passed

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tessl review fix ./.codex/skills/aiox-data-engineer/SKILL.md

Quality

Content

82%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 body is a tight, well-structured activator with concrete commands and a clear activation sequence, respecting the token budget while remaining actionable; its main weakness is that the detailed persona/command system lives in out-of-bundle files rather than in well-signaled one-level-deep references.

Suggestions

Add a brief validation/confirmation step to the Activation Protocol (e.g., 'Confirm greeting rendered before proceeding') to strengthen workflow_clarity.

Either bundle the referenced persona/command files under references/ and link them as one-level-deep markdown references, or note explicitly that the .aiox-core paths are project-external so navigation expectations are clear.

Inline one or two example command outputs (e.g., a sample '*help' result) to push actionability toward copy-paste-ready completeness.

Dimension	Reasoning	Score
Conciseness	The body is extremely lean — short sectioned lists with concrete commands and file paths and no padding or explanation of concepts Claude already knows — so every token earns its place, matching the 'lean and efficient; assumes Claude's competence' (5) anchor.	5 / 5
Actionability	Provides concrete executable commands such as 'node .aiox-core/development/scripts/generate-greeting.js data-engineer' and specific starter commands ('create-schema', 'create-rls-policies'), but the full persona/command system lives in referenced external files, leaving minor gaps versus copy-paste-ready completeness (5).	4 / 5
Workflow Clarity	The Activation Protocol is a clear numbered 4-step sequence, and as a single-purpose persona activator with no destructive/batch operations the simple-skill exception applies; it lacks explicit validation checkpoints, so it sits at 'clear sequence with most checkpoints present, minor gaps' (4) rather than (5).	4 / 5
Progressive Disclosure	Content is well-organized into clearly labeled sections (When To Use, Activation Protocol, Starter Commands, Non-Negotiables) and points to specific external files, but the referenced paths live outside the skill bundle (no references/scripts/assets dirs present) and are not signaled as one-level-deep bundle references, fitting the 'good structure, minor organization gaps' (4) anchor rather than (5).	4 / 5
	Total	17 / 20 Passed

Description

75%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 clearly communicates a distinct DBA/Supabase niche with multiple concrete capabilities and an explicit 'Use for' trigger, but the trailing ellipsis truncation and lack of richer trigger synonyms keep it just below top marks across all dimensions.

Suggestions

Complete the truncated 'data modelin...' so the full capability list is present and not cut off.

Add natural trigger synonyms and file/tech cues users actually say (e.g., 'PostgreSQL', 'Postgres', 'row-level security', 'schema migrations') to strengthen trigger_term_quality.

Make the 'when' more explicit with a concrete phrasing like 'Use when the user needs database design, Supabase RLS setup, schema migrations, or query optimization.'

Dimension	Reasoning	Score
Specificity	Lists several specific concrete actions — 'database design, schema architecture, Supabase configuration, RLS policies, migrations, query optimization' — but the trailing 'data modelin...' truncation leaves minor coverage gaps, sitting between the 'several specific actions' (4) and 'comprehensive coverage' (5) anchors.	4 / 5
Completeness	Provides a clear 'what' (the enumerated DBA capabilities) and an explicit 'when' via the 'Use for ...' clause, but the 'when' could be more explicit/specific (no 'when the user mentions X' phrasing) and the truncation weakens it, placing it at the 'both present, when could be more explicit' (4) anchor rather than (5).	4 / 5
Trigger Term Quality	Includes natural user-facing terms like 'database design', 'Supabase', 'RLS policies', 'migrations', and 'query optimization' that users would actually say, but is missing a few common synonyms/variations, fitting the 'good keyword coverage, a few natural terms missing' anchor rather than the comprehensive (5) anchor.	4 / 5
Distinctiveness Conflict Risk	The Supabase/RLS/DBA niche is mostly distinct with clear triggers, but broader terms like 'data modeling' and 'query optimization' risk minor overlap with general development skills, matching the 'mostly distinct; minor overlap risk' (4) anchor rather than the minimal-conflict (5) anchor.	4 / 5
	Total	16 / 20 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: SynkraAI/aiox-core
Path: .codex/skills/aiox-data-engineer/SKILL.md
Commit: 4ef6530

Reviewed: 1 day ago

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