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postgresql-table-design

Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

1.27x
Quality

67%

Does it follow best practices?

Impact

92%

1.27x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./tests/ext_conformance/artifacts/agents-wshobson/database-design/skills/postgresql/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%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 strong, information-dense PostgreSQL design reference with genuinely actionable DDL and well-chosen gotchas, held back by its shape rather than its substance: it is a flat topic-by-topic reference with no sequenced design workflow or validation checkpoints, and no progressive disclosure into reference files despite covering ~15 distinct topic areas in one file. Tightening the longest bullets and splitting extensions/JSONB detail into references would lift the two weakest dimensions.

Suggestions

Add a short sequenced design workflow (e.g., define access patterns → choose types → apply Core Rules → add indexes/constraints → test DDL in a transaction and roll back) with an explicit validation checkpoint, which would also satisfy the database-operations feedback-loop requirement.

Move the Extensions list and the JSONB guidance (opclass trade-offs, generated-column extraction) into a references/ file and link them one level deep from SKILL.md, keeping the core rules and examples inline.

Split the overloaded Strings bullet (TOAST strategies, collations, CITEXT) into separate short entries or a reference, and complete fragmentary snippets like the RLS policy example.

DimensionReasoningScore

Conciseness

The body is dense and rule-oriented ('Heap storage: no clustered PK by default... CLUSTER is one-off reorganization'), assuming Claude already knows PostgreSQL basics rather than explaining them. A few entries run long (the Strings bullet packs TOAST strategies, collations, and CITEXT into one paragraph) and could be trimmed, keeping it below the 'lean, every token earns its place' anchor.

4 / 5

Actionability

Most guidance is executable — concrete DDL like 'CREATE INDEX ON tbl (user_id) WHERE status = 'active'' and complete copy-paste example tables (users, orders, profiles). Some entries remain fragmentary ('FOR VALUES IN ('us-east', 'us-west')', 'CREATE POLICY user_access ON orders ... USING (user_id = current_user_id())' referencing an undefined function), so it stops short of fully copy-paste-ready coverage.

4 / 5

Workflow Clarity

This is reference material organized by topic, not a sequenced design workflow — there is no 'analyze access patterns → define types → add constraints → index → validate' order. The rubric's scoring note caps database-operation skills without explicit validate/fix/retry feedback loops at 3; 'Safe Schema Evolution' offers transactional-DDL testing ('BEGIN; ALTER TABLE...; ROLLBACK;') but no explicit validation checkpoints, so 3 is the ceiling and also the best fit.

3 / 5

Progressive Disclosure

Sections are clearly headed (Core Rules, Data Types, Indexing, Partitioning, Examples), but the entire ~200-line reference lives in SKILL.md with no bundle files and no offloading — the Extensions list, JSONB deep-dive, and TOAST/collation details are exactly the material the anchor-3 example describes as inline content that could live in separate reference files.

3 / 5

Total

14

/

20

Passed

Description

53%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 states what the skill does and is well-scoped to PostgreSQL schema work, but it entirely lacks a 'when to use' clause and natural trigger phrasing, which caps both completeness and trigger-term quality. Adding an explicit usage trigger with common synonyms (Postgres, database tables, schema design/migration) would move it into the good-example range.

Suggestions

Append an explicit trigger clause, e.g., 'Use when creating or modifying PostgreSQL tables, designing a database schema, choosing column types, or adding indexes/constraints to Postgres tables.'

Include natural variations users actually say — 'Postgres', 'database schema', 'table design', 'schema migration' — to broaden trigger-term coverage.

Consider naming one or two more concrete actions (e.g., 'choose data types, plan indexing and partitioning') instead of the generic 'Covers best-practices ... and advanced features' tail, which reads as padding.

DimensionReasoningScore

Specificity

It names the domain ('PostgreSQL-specific schema') and one concrete action ('Design'), then lists topics ('data types, indexing, constraints, performance patterns') rather than actions. That matches 'names domain and 1-2 concrete actions, but not comprehensive' — it is above score 2 (the domain is concrete, not generic) but does not list the several specific actions the score-4 anchor requires.

3 / 5

Completeness

The 'what' is clear (design a PostgreSQL schema covering types, indexing, constraints, performance), but there is no 'Use when...' clause or any trigger guidance at all; the rubric explicitly caps completeness at 3 for a missing when-clause, which this description has.

3 / 5

Trigger Term Quality

'PostgreSQL', 'schema', 'data types', 'indexing', and 'constraints' are relevant keywords a user might say, but common natural variations are missing — 'Postgres', 'database', 'tables', 'SQL', 'schema migration'. That fits 'some relevant keywords but missing common variations or synonyms', below score 4's 'a few natural terms missing'.

3 / 5

Distinctiveness Conflict Risk

'PostgreSQL-specific schema' pins the database engine and task, so it is mostly distinct with only minor overlap risk against generic SQL/database-design or migration skills — matching score 4. It falls short of score 5 because without trigger phrases there is no explicit niche signal separating it from, say, a PostgreSQL query-tuning or migration skill.

4 / 5

Total

13

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Dicklesworthstone/pi_agent_rust

Path

tests/ext_conformance/artifacts/agents-wshobson/database-design/skills/postgresql/SKILL.md

Reviewed

Table of Contents

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