CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

sql-pro

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Quality

52%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/sql-pro/SKILL.md

The canonical home for this skill is sql-pro in rmyndharis/antigravity-skills

SKILL.md
Quality
Evals
Security

Quality

Content

35%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 persona résumé: an expansive catalog of databases, techniques, and traits that assumes Claude knows nothing, while providing zero executable guidance — no example queries, no EXPLAIN workflows, no concrete tuning steps. It works only as a vague scope-setter; almost all of it could be cut or moved to references without loss.

Suggestions

Replace the Capabilities/Behavioral Traits/Knowledge Base catalogs with a small set of concrete workflows: an example query-optimization loop (run EXPLAIN, read the plan, add/adjust an index, re-run), a schema-design checklist, and one or two executable SQL examples.

Move any retained domain catalogs (engine-specific syntax, index strategy details) into a references/ file and link them one level deep from SKILL.md.

Cut the duplicated 'Purpose' section (it restates the frontmatter description) and keep the 'Use/Do not use this skill when' lists, which are the most useful part of the body.

DimensionReasoningScore

Conciseness

Roughly 130 of 172 lines are capability catalogs ("Cloud-native databases: Amazon Aurora, Google Cloud SQL...", "Knowledge Base", "Behavioral Traits") that restate what Claude already knows about databases — several heavily padded sections with no new information, matching 'noticeably verbose'.

2 / 5

Actionability

The Instructions offer only high-level hints ("Inspect schema, statistics, and access paths", "Optimize queries and validate with EXPLAIN") with no code, commands, or specific steps; the Capabilities sections describe rather than instruct, matching 'minimal concrete guidance'.

2 / 5

Workflow Clarity

The four Instructions steps are sequenced and mention validation ("Verify correctness and performance under load"), but there is no feedback loop for error recovery, and database operations without explicit validation feedback loops are capped at 3 per the scoring notes.

3 / 5

Progressive Disclosure

Section headers organize the body, but the large capability catalog that belongs in reference files (or nowhere) is fully inlined, and the bundle contains no references/, scripts/, or assets/ files — matching 'some structure but content that should be separate is inline'.

3 / 5

Total

10

/

20

Passed

Description

48%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 identifies a clear SQL niche with relevant domain keywords, but reads like a résumé headline rather than a trigger description: no 'use when' guidance, no concrete actions, and an imperative voice instead of third person. Users needing SQL help would likely match it, but so would many adjacent data tasks.

Suggestions

Rewrite in third person with concrete actions, e.g. 'Writes and optimizes SQL queries, designs schemas for OLTP/OLAP workloads, and tunes performance via indexes and query plans.'

Add an explicit 'Use when...' clause: 'Use when writing or optimizing SQL queries, designing database schemas, or analyzing query plans.'

Include natural user phrases like 'slow query', 'index', 'EXPLAIN plan', and specific engines (PostgreSQL, Snowflake) to improve trigger matching.

DimensionReasoningScore

Specificity

"Master modern SQL with cloud-native databases... Expert in performance tuning, data modeling" names broad domains with generic action nouns rather than concrete actions (no 'writes queries', 'tunes indexes', 'designs schemas'). The imperative 'Master...' is not third-person voice, which the guidelines penalize by reducing specificity by 1 from a base of 3.

2 / 5

Completeness

The 'what' is reasonably clear (SQL expertise across optimization, tuning, data modeling) but the 'when' is entirely absent — there is no 'Use when...' clause or equivalent trigger guidance, capping completeness at 3.

3 / 5

Trigger Term Quality

Terms like "SQL", "OLTP/OLAP", "query", and "performance tuning" are relevant keywords, but common variations users naturally say ("database", "index", "query plan", "slow query") are missing, matching the 'some relevant keywords but missing common variations' anchor.

3 / 5

Distinctiveness Conflict Risk

"Master modern SQL" carves a clear niche with a distinct trigger term, though "data modeling" and broad cloud/OLAP coverage create minor overlap risk with data-engineering or backend skills, matching 'mostly distinct; minor overlap risk'.

4 / 5

Total

12

/

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.

Validation — 15 / 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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/sql-pro/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.