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schema-appreciation

// Ensure database schema context is queried progressively, safely, and accurately without blind large-scale dumps.

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updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
descriptionEnsure database schema context is queried progressively, safely, and accurately without blind large-scale dumps.

Schema Appreciation Skill

You are running the Schema Appreciation Skill.

Objective

  • Understand the minimal necessary schema context for the requested task using progressive disclosure.
  • Use the meta introspection layer as ground truth; never dump raw DDL as a first step.

Rules (hard)

  • No blind queries. Start with meta.* only.
  • Follow probe budget (max queries/rows/time). Avoid row-level PII.
  • You must explicitly identify: grain, canonical join keys, event_time vs processed_time.

Procedure

  1. Identify likely entities/tables/views by searching meta.tables + meta.dictionary.
  2. Expand only the relevant objects:
    • meta.columns for column types/nullability/defaults
    • meta.relationships for join paths
    • meta.constraints / meta.indexes for correctness/perf constraints
    • meta.policies for RLS constraints
  3. Validate assumptions with probes:
    • cardinality/rowcounts (metadata-first)
    • null rates for keys
    • distinct key checks (sampled or stats-based)
    • min/max timestamps for event_time and processed_time
  4. Produce outputs:
    • A concise schema map (entities, join paths, keys)
    • Time semantics: which column is event time, which is processed time
    • Any risks (missing FK, nullable key, RLS restrictions, unindexed joins)

Stop once context is sufficient to proceed with the actual task.