managing-database-partitions

Name: managing-database-partitions
Rating: 51 (1 reviews)
Author: jeremylongshore

tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill managing-database-partitions

github.com/jeremylongshore/claude-code-plugins-plus-skills

Process use when you need to work with database partitioning. This skill provides table partitioning strategies with comprehensive guidance and automation. Trigger with phrases like "partition tables", "implement partitioning", or "optimize large tables".

Review Score

51%

Validation Score

13/16

Implementation Score

Activation Score

90%

SKILL.md

Review

Evals

Generated

11 days ago

Warnings & errors only

Criteria	Score
allowed_tools_field	'allowed-tools' contains unusual tool name(s)
metadata_version	'metadata' field is not a dictionary
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata

Overall Assessment

This skill is a generic template with no actual database partitioning content. It provides abstract software development lifecycle steps that could apply to any technical task, completely failing to teach Claude anything specific about partition strategies (range, list, hash), partition maintenance, or partition-specific SQL syntax. The skill wastes tokens on boilerplate while providing zero actionable partitioning guidance.

Suggestions

Add concrete SQL examples for creating partitions (e.g., CREATE TABLE with PARTITION BY RANGE/LIST/HASH syntax for PostgreSQL, MySQL, or target database)
Include specific partition maintenance commands: adding/dropping partitions, partition pruning verification, and data migration between partitions
Replace generic SDLC steps with partitioning-specific workflow: analyze table size/access patterns → choose partition strategy → implement partition scheme → validate partition pruning in query plans → monitor partition distribution
Add decision criteria for choosing partition types (range for time-series, list for categorical, hash for even distribution) with concrete examples

Dimension	Score	Reasoning
Conciseness	1/3	Extremely verbose with generic boilerplate that applies to any task. Contains no database partitioning-specific content - just generic software development lifecycle steps that Claude already knows. Every section could apply to literally any technical task.
Actionability	1/3	No concrete code, SQL examples, or specific partitioning commands. Entirely abstract guidance like 'Review current configuration' and 'Define optimal approach' without any executable examples of partition creation, maintenance, or management.
Workflow Clarity	1/3	While steps are numbered, they are generic SDLC phases with no partitioning-specific validation. Missing critical partitioning workflows like: checking partition alignment, validating partition pruning, testing partition switching, or verifying data distribution across partitions.
Progressive Disclosure	2/3	References external files in a structured way (templates, docs, examples directories), but the main content is a wall of generic text. The referenced files appear to be placeholders rather than real resources, and the skill body itself lacks any substantive content to disclose progressively.

Overall Assessment

This description has strong trigger term coverage and completeness with explicit usage guidance. The main weakness is the lack of specific concrete actions - it describes the domain well but doesn't enumerate what specific partitioning operations it can perform (e.g., range vs hash partitioning, partition maintenance, migration strategies).

Suggestions

Add specific concrete actions like 'create range/hash/list partitions', 'migrate existing tables to partitioned schemas', 'analyze partition performance', or 'manage partition maintenance'

Dimension	Score	Reasoning
Specificity	2/3	Names the domain (database partitioning) and mentions 'table partitioning strategies' and 'automation', but lacks specific concrete actions like 'create range partitions', 'migrate existing tables', or 'analyze partition performance'.
Completeness	3/3	Clearly answers both what ('table partitioning strategies with comprehensive guidance and automation') and when ('Trigger with phrases like...' provides explicit trigger guidance). Has explicit 'Use when' equivalent clause.
Trigger Term Quality	3/3	Explicitly lists natural trigger phrases users would say: 'partition tables', 'implement partitioning', 'optimize large tables'. These are realistic terms a user would naturally use when needing this skill.
Distinctiveness Conflict Risk	3/3	Database partitioning is a clear niche with distinct triggers. Terms like 'partition tables' and 'implement partitioning' are specific enough to avoid conflicts with general database or optimization skills.