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find-hypertable-candidates

Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.

74

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with executable SQL and a concrete scoring rubric, a clear two-step workflow, and well-organized sections. The only weakness is mild verbosity from restating good/poor patterns in prose that could be tightened.

Suggestions

Tighten the good/poor pattern lists in Step 1 — they repeat information already conveyed by the SQL 'Look for' callouts and the Common Patterns section, so consider consolidating to reduce token usage.

The 'TimescaleDB Benefits' opening could be trimmed to a one-line summary of gains, since the detailed benefit enumeration is context Claude largely already knows.

DimensionReasoningScore

Conciseness

The body is mostly efficient (SQL snippets, a scoring rubric, example tables) and avoids teaching concepts Claude already knows, but the good/poor pattern lists are restated in prose and the document could be tightened; it sits between the lean and slightly-padded anchors.

2 / 3

Actionability

It provides executable SQL queries throughout, a concrete point-based scoring rubric, and copy-paste-ready table examples with explicit partition/segment/sparse-index directives, matching the fully-executable anchor.

3 / 3

Workflow Clarity

Step 1 (schema analysis, with Options A/B) and Step 2 (candidacy scoring) are clearly sequenced, and the "Analysis Output Requirements" section acts as a per-table checklist; the queries are read-only analysis rather than destructive batch operations, so the missing-feedback-loop cap does not apply.

3 / 3

Progressive Disclosure

This is a single self-contained SKILL.md with no bundle files and well-organized sections (Benefits, Step 1, Step 2, Common Patterns, Output Requirements); the only external reference is a clearly signaled companion skill, which is appropriate and one level deep.

3 / 3

Total

11

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12

Passed

Description

100%Weight 40%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: concrete actions, explicit trigger guidance, natural keywords, and a distinct niche with no conflict risk. Third-person voice is maintained throughout.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "analyze an existing PostgreSQL database and identify which tables should be converted", "Provides SQL queries to analyze table statistics, index patterns, and query patterns", and "Includes scoring criteria (8+ points = good candidate)" — matching the multiple-specific-actions anchor.

3 / 3

Completeness

It explicitly answers both what (analyze DB, identify tables, provide SQL queries and scoring criteria) and when via the explicit "Trigger when user asks to" clause plus keywords, satisfying the what-AND-when anchor.

3 / 3

Trigger Term Quality

It provides both a "Trigger when user asks to:" bulleted list and a "Keywords:" line with natural terms users would say (hypertable candidate, table analysis, migration assessment, Timescale, time-series detection, event logs, audit tables), giving good coverage of natural variations.

3 / 3

Distinctiveness Conflict Risk

The niche is narrow and specific (TimescaleDB hypertable candidacy), triggers are distinct, and it references a companion migration skill; it uses third person and is unlikely to trigger for the wrong skill.

3 / 3

Total

12

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
timescale/pg-aiguide
Reviewed

Table of Contents

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