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sql-analyst

SQL query expert for optimization, schema design, and data analysis

55

Quality

61%

Does it follow best practices?

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tessl review fix ./crates/openfang-skills/bundled/sql-analyst/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%

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 concise, well-organized reference of SQL best practices that respects Claude's existing knowledge and stays token-efficient. Its main gaps are the absence of any complete runnable example query and the lack of an explicit validation/feedback loop for destructive or batch database operations.

Suggestions

Add one or two complete, executable example queries (e.g., a keyset-pagination query and an EXPLAIN-verified optimization before/after) to lift actionability to fully copy-paste ready.

For risky operations (schema migrations, bulk writes, adding indexes), include an explicit validate→fix→retry loop, e.g., run EXPLAIN ANALYZE before/after, test on a copy, and verify row counts before committing.

Consider splitting the optimization and schema sections into referenced detail files only if the content grows; at its current size the inline organization is already appropriate.

DimensionReasoningScore

Conciseness

The body is lean bullet guidance that assumes Claude already knows SQL, with parentheticals only for genuinely non-obvious points (CTE materialization, function-on-index blocking index use). Not 2 because there is no padding or unnecessary concept explanation; every bullet earns its place.

3 / 3

Actionability

Directives are concrete and specific ("Use EXISTS instead of IN," "WHERE id > last_seen_id," "TIMESTAMP WITH TIME ZONE," anti-pattern "WHERE YEAR(created_at) = 2025"), but there are no complete executable example queries or copy-paste snippets. Not 3 because no runnable code block is provided; not 1 because the guidance is specific and actionable rather than abstract.

2 / 3

Workflow Clarity

Content is well organized by category and the "Pitfalls to Avoid" section plus "use EXPLAIN or EXPLAIN ANALYZE" and "Do not add indexes without measuring" act as implicit checkpoints, but there is no explicit validate→fix→retry feedback loop for risky write/batch operations (migrations, indexing, bulk updates), which the notes say should cap this at 2. Not 1 because sequencing/checkpoints are partly present; not 3 because no explicit feedback loop is defined.

2 / 3

Progressive Disclosure

The skill is under 50 lines, single-purpose with no bundle files, and is organized into clear labeled sections (Key Principles, Query Optimization, Schema Design, Analysis Patterns, Pitfalls). Per the guideline, this can score 3 on well-organized sections alone; not 2 because the structure is clean and there are no nested references.

3 / 3

Total

10

/

12

Passed

Description

50%

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 concise and in correct third-person voice, clearly stating the skill's domain and broad capabilities, but it lacks explicit "Use when..." trigger guidance and lists only high-level action categories rather than concrete operations. It is solid but generic enough to risk overlap with adjacent skills.

Suggestions

Add an explicit "Use when..." clause naming concrete trigger scenarios (e.g., "Use when writing, optimizing, or debugging SQL queries across PostgreSQL, MySQL, and SQLite, or when designing database schemas").

Replace broad categories ("optimization, schema design, data analysis") with several concrete actions (e.g., "rewrite slow queries, add indexes, normalize schemas, build window-function analytics") to improve specificity and trigger coverage.

Include natural trigger keywords users would actually say (e.g., "slow query," "joins," "indexes," "EXPLAIN," "query tuning") to strengthen distinctiveness.

DimensionReasoningScore

Specificity

"optimization, schema design, and data analysis" names the SQL domain and several broad action areas, but these are high-level categories rather than multiple concrete actions like "extract text, fill forms, merge documents." Not 3 because the actions are not granular/specific; not 1 because genuine actions are named.

2 / 3

Completeness

It clearly states what the skill does ("SQL query expert for optimization, schema design, and data analysis") but has no "Use when..." clause or equivalent explicit trigger for when Claude should invoke it, which per the guidelines caps completeness at 2. Not 1 because the "what" is solid; not 3 because the "when" is entirely absent.

2 / 3

Trigger Term Quality

"SQL query," "optimization," "schema design," and "data analysis" are natural terms a user might say, but coverage of common variations (joins, indexes, query tuning, specific dialects) is missing. Not 3 because the keyword set is incomplete; not 1 because the terms are genuinely natural rather than jargon.

2 / 3

Distinctiveness Conflict Risk

"SQL query expert" carves a recognizable niche, but the broad "optimization" and "data analysis" framing could overlap with general data or code skills. Not 3 because the triggers are not distinctive enough to rule out overlap; not 1 because SQL is a concrete, bounded domain.

2 / 3

Total

8

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
RightNow-AI/openfang
Reviewed

Table of Contents

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