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setup-timescaledb-hypertables

Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. **Trigger when user asks to:** - Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available - Set up hypertables, compression, retention policies, or continuous aggregates - Configure partition columns, segment_by, order_by, or chunk intervals - Optimize time-series database performance or storage - Create tables for sensors, metrics, telemetry, events, or transaction logs **Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.

71

Quality

89%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

A highly actionable, well-sequenced setup guide with executable SQL at every step and explicit end-to-end verification. Its weaknesses are mild redundancy and general-Postgres filler, plus a monolithic single-file layout with no progressive disclosure into reference files despite being long enough to warrant it.

Suggestions

Split stable reference material (deprecated-vs-current API mapping, schema best-practices checklist, sparse index reference) into files under references/ and link them from short SKILL.md sections, moving the body toward an overview-plus-detail structure.

Trim the Do's and Don'ts list to the TimescaleDB-specific items (TIMESTAMPTZ, time_bucket usage) and drop general PostgreSQL conventions Claude already knows, and de-duplicate the chunk-size guidance repeated in both the chunk-interval section and Performance Guidelines.

Add a short error-recovery step after Step 11 verification: what to check and fix when chunks remain uncompressed, jobs fail, or aggregate refresh falls behind, turning the verify queries into a validate→fix→retry loop.

DimensionReasoningScore

Conciseness

The body is dense with genuinely non-obvious, domain-specific guidance (row-density thresholds, tsdb.* DDL options, deprecated→current API mapping) and avoids explaining basics, so it is mostly efficient. However, the Do's and Don'ts list reiterates general PostgreSQL practices Claude already knows ("Use snake_case NOT CamelCase", "Use NOT EXISTS NOT NOT IN"), and some guidance (chunk-size test, retention caution) is repeated across sections — minor over-explanation that could be trimmed, fitting the level-4 anchor rather than the lean level-5 anchor.

4 / 5

Actionability

Every step ships copy-paste-ready SQL with placeholders: the CREATE TABLE ... WITH (tsdb.hypertable, ...) template, ALTER TABLE columnstore settings, add_retention_policy/add_continuous_aggregate_policy calls, index DDL, and verification queries. The examples cover the common cases (IoT, finance, metrics, event logs) with concrete parameter values, matching the fully-executable top anchor.

5 / 5

Workflow Clarity

Steps 1–11 form a clear, well-ordered sequence, and Step 11 provides explicit verification queries (hypertables, compression stats, jobs, chunks) — so the destructive/batch-operation validation cap at 3 does not apply. It falls short of the level-5 anchor because there is no error-recovery feedback loop (e.g., what to do when verify queries show uncompressed chunks or a misconfigured policy) and some checkpoints (e.g., the segment_by 'good test') are stated but not tied back into a validation step.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent) and the ~475-line body keeps everything inline — including an API reference section and schema best-practices list that would naturally live in referenced files. Section headers do give reasonable in-file organization, but there is no overview-to-detail split across files, fitting 'some structure but could be better organized; content that should be separate is inline'.

3 / 5

Total

16

/

20

Passed

Description

96%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.

A strong description: it explicitly states both what it does and when to use it, with a rich, natural keyword set and concrete trigger bullets. The only weakness is the unscoped 'any insert-heavy table' performance claim, which slightly broadens the trigger surface beyond the TimescaleDB niche.

DimensionReasoningScore

Specificity

The closing line lists six concrete actions — "hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes" — giving comprehensive, specific coverage of the domain rather than vague claims. It matches the 'lists multiple specific concrete actions; comprehensive coverage' anchor; the level-4 anchor's 'minor gaps in coverage' does not apply.

5 / 5

Completeness

It explicitly answers 'what' ("Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes") and 'when' with a concrete "**Trigger when user asks to:**" bullet list plus a keywords section. Both are explicit with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

The keywords list combines natural user phrasing ("time-series", "IoT", "metrics", "sensor data", "CREATE TABLE") with technical synonyms and parameter names ("hypertable", "columnstore", "segment_by", "chunk interval"), plus domain aliases (Timescale, TimescaleDB, TigerData, Tiger Cloud). Coverage is comprehensive including synonyms; only file extensions are absent, which do not apply to this domain.

5 / 5

Distinctiveness Conflict Risk

The niche is clear and triggers are highly Timescale-specific (hypertable, segment_by, columnstore), but the unscoped claim "Use this to improve the performance of any insert-heavy table" carries minor overlap risk with generic database-tuning skills. This fits 'mostly distinct; minor overlap risk with closely related skills' rather than the 'minimal conflict risk' of the top anchor.

4 / 5

Total

19

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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

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
timescale/pg-aiguide
Reviewed

Table of Contents

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