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postgresql-database-engineering

Comprehensive PostgreSQL database engineering skill covering indexing strategies, query optimization, performance tuning, partitioning, replication, backup and recovery, high availability, and production database management. Master advanced PostgreSQL features including MVCC, VACUUM operations, connection pooling, monitoring, and scalability patterns.

Quality

62%

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tessl review fix ./plugins/luxor-database-pro/skills/postgresql-database-engineering/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 body reads as a PostgreSQL encyclopedia rather than a skill: it is rich in executable SQL and config examples, but buries them in long explanations of concepts Claude already knows, with no progressive disclosure into reference files and no validation checkpoints around destructive operations. The token cost of loading this skill is enormous relative to the incremental knowledge it adds.

Suggestions

Split the body into one-level-deep reference files (e.g., references/indexing.md, references/partitioning.md, references/replication.md, references/backup-pitr.md, references/monitoring.md) and keep SKILL.md as a concise overview with a 'When to use' section and pointers.

Delete sections explaining knowledge Claude already has (MVCC theory, isolation levels, join types, PostgreSQL architecture) and keep only PostgreSQL-specific decision guidance, e.g., the index-type decision matrix and tuning value recommendations.

Add validation checkpoints around destructive workflows — e.g., verify pg_basebackup completed and verify standby is in recovery before stopping the primary, and check replication lag before detaching/dropping partitions in the maintenance flow.

DimensionReasoningScore

Conciseness

The ~1260-line body extensively explains concepts Claude already knows — PostgreSQL process architecture, MVCC ('No read locks - readers never block writers'), the four isolation levels, join methods (nested loop/hash/merge), and index type fundamentals. This is textbook reference material padded into a skill file, matching the anchor for severely verbose content that explains known concepts.

1 / 5

Actionability

Most sections provide concrete, copy-paste-ready SQL, conf, and bash (EXPLAIN ANALYZE examples, a partition-creation plpgsql function, pg_basebackup/PITR commands, monitoring queries against pg_stat_* views). It is not a 5 because some examples contain gaps or errors — e.g., the backfill step uses 'UPDATE users SET email_verified = false ... LIMIT 10000', which is not valid PostgreSQL syntax.

4 / 5

Workflow Clarity

Multi-step processes like PITR recovery, streaming replication setup, and controlled switchover have numbered sequences, but destructive operations (rm -rf of the data directory, DROP TABLE of partitions, standby rebuild) include no validation or verification checkpoints. The rubric explicitly caps workflow clarity at 3 when destructive/batch operations lack validation.

3 / 5

Progressive Disclosure

The skill is entirely monolithic: no references/, scripts/, or assets/ directories exist, and all ~1200 lines — including deep reference material like full-text search setup, FDW configuration, and diagnostic query catalogs — are inlined in SKILL.md. This matches the anchor for content that clearly belongs in separate files being inlined, though section headers provide some structure above a score of 1.

2 / 5

Total

10

/

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.

The description clearly communicates a broad PostgreSQL engineering scope with strong, natural trigger terms and excellent distinctiveness. Its main weakness is the complete absence of explicit 'when to use' guidance, which caps its completeness and overall effectiveness as a trigger description.

Suggestions

Add an explicit trigger clause, e.g., 'Use when the user mentions PostgreSQL, slow queries, index tuning, replication setup, VACUUM/maintenance issues, or database performance problems.'

Convert topic nouns into concrete actions (e.g., 'Designs indexes and partitioning schemes, optimizes slow queries with EXPLAIN, configures streaming replication and failover, automates backups and PITR') to sharpen specificity.

Trim stacked buzzwords like 'Comprehensive', 'Master advanced', and 'scalability patterns' — they add length without adding trigger value.

DimensionReasoningScore

Specificity

The description lists many concrete capability areas — 'indexing strategies, query optimization, performance tuning, partitioning, replication, backup and recovery, high availability' — giving broad, specific coverage of the domain. It falls short of a 5 because it names topic areas rather than concrete actions (no verb-driven capabilities like 'design schemas' or 'tune queries'), and well above 3 since far more than 1-2 areas are covered.

4 / 5

Completeness

The 'what' is clear and comprehensive ('Comprehensive PostgreSQL database engineering skill covering indexing strategies, query optimization...'), but there is no 'Use when...' clause or any equivalent trigger guidance for when to invoke the skill. Per the rubric guideline, a missing 'when' clause caps completeness at 3.

3 / 5

Trigger Term Quality

Strong natural keywords users would actually say: 'PostgreSQL', 'indexing', 'query optimization', 'replication', 'backup and recovery', 'connection pooling', 'monitoring'. A few common natural phrases are missing (e.g., 'slow queries', 'schema design', 'database migration'), which keeps it at 4 rather than 5.

4 / 5

Distinctiveness Conflict Risk

The description is unambiguously PostgreSQL-specific (MVCC, VACUUM operations, PostgreSQL feature names), occupying a clear niche with minimal overlap risk against other skills. It matches the anchor for a clear niche with distinct triggers.

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (1265 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository

manutej/luxor-claude-marketplace

Path

plugins/luxor-database-pro/skills/postgresql-database-engineering/SKILL.md

Reviewed

Table of Contents

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