archiving-databases
tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill archiving-databasesProcess use when you need to archive historical database records to reduce primary database size. This skill automates moving old data to archive tables or cold storage (S3, Azure Blob, GCS). Trigger with phrases like "archive old database records", "implement data retention policy", "move historical data to cold storage", or "reduce database size with archival".
Validation
81%| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 13 / 16 Passed | |
Implementation
20%This skill reads like a generic process document rather than actionable guidance for Claude. It lacks any concrete code examples, SQL queries, or executable commands despite being a technical database task. The verbose step-by-step format explains what to do conceptually but never shows how to do it, making it nearly useless for actual implementation.
Suggestions
Add concrete SQL examples for common archival patterns (e.g., INSERT INTO archive_table SELECT * FROM source WHERE created_at < NOW() - INTERVAL '1 year'; DELETE FROM source WHERE id IN (SELECT id FROM archive_table))
Include a minimal working Python/shell script showing the extract-verify-delete pattern with actual code
Replace the 30-step checklist with a concise quick-start section showing the core archival workflow in under 20 lines
Add explicit validation gates inline: 'STOP: Verify row counts match before proceeding to delete' rather than burying verification in separate sections
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive padding and generic instructions that Claude already knows. The 6-step process with 5 sub-steps each reads like a tutorial for beginners rather than actionable guidance for an AI assistant. Phrases like 'Understanding of data retention requirements' and 'Document business requirements' add no value. | 1 / 3 |
Actionability | No executable code, SQL examples, or concrete commands anywhere. Instructions are entirely abstract ('Write SQL query to identify records', 'Create extraction script') without showing actual implementation. References to template files that may not exist don't compensate for missing concrete examples. | 1 / 3 |
Workflow Clarity | Steps are sequenced and include some validation mentions (Step 5 mentions verification, error handling covers integrity checks). However, validation checkpoints are not explicit inline with the workflow - they're separated into a generic error handling section rather than integrated as 'validate before proceeding' gates. | 2 / 3 |
Progressive Disclosure | References external files (templates, scripts, policies) which is good structure, but the main content is a monolithic wall of numbered lists. The 'Overview' and 'Examples' sections at the end are empty placeholders that add nothing. Content could be better organized with quick-start vs detailed sections. | 2 / 3 |
Total | 6 / 12 Passed |
Activation
100%This is a well-crafted skill description that excels across all dimensions. It provides specific actions, excellent trigger term coverage with natural user phrases, clearly answers both what and when, and occupies a distinct niche in database archival. The only minor issue is the awkward phrasing 'Process use when' at the start, but this doesn't significantly impact functionality.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'archive historical database records', 'moving old data to archive tables or cold storage', and names specific storage targets (S3, Azure Blob, GCS). | 3 / 3 |
Completeness | Clearly answers both what (automates moving old data to archive tables or cold storage) and when (explicit 'Use when' equivalent with 'Trigger with phrases like...' providing clear activation guidance). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger phrases users would say: 'archive old database records', 'data retention policy', 'move historical data to cold storage', 'reduce database size with archival'. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused specifically on database archival and data retention - distinct triggers like 'archive historical database records' and 'cold storage' are unlikely to conflict with general database or file management skills. | 3 / 3 |
Total | 12 / 12 Passed |
Reviewed
Table of Contents
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