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HainrixzHainrixz/claude-db/skills/explain/SKILL.md

explain

Skill22 starsChanged 5 months agoMITView on GitHub

Explain a database schema, model, or a single finding in plain language, with a paradigm-aware diagram — what the tables/collections/keyspaces are, how they relate, and where the data lives. Read-only; teaches, does not change anything. Use when the user asks to explain, describe, walk through, draw, or diagram a schema, a data model, a relationship, or what a specific audit finding means.

122 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 109 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If the target is a finding id, explain what it checks, which score/axis it affects (design | performance | both), why it matters, and how …

    line 27
  2. Very specific:

    If the user wants a live plan generated for them (running EXPLAIN against their database) rather than pasting one, mark the request …

    line 33

“Common” is measured: kept by at least 6 in 10 of the 109 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- Copyright (c) 2026 Enrique Rocha (@soyenriquerocha) · tododeia.com · id er-f37b7121 -->

/claude-db:explain

Plain-language description of a schema (or one finding), plus a paradigm-aware diagram. Read-only — explains, never edits or migrates.

$ARGUMENTS = <path|table|finding-id> [flags]. The target can be a schema/ORM/migration path, a single table/collection name, or a finding id from a prior audit.

What to do

  1. Detect the paradigm/engine (scripts/detect-stack.mjs) and parse the model (scripts/parse-schema.mjs / parse-orm-python.py).
  2. Give a plain-language description first — no jargon in the opening: what each entity holds, who owns what, and how the pieces connect, in the user's words ("a user has many orders; each order belongs to exactly one user").
  3. Render a paradigm-aware diagram (Mermaid) with node scripts/gen-diagram.mjs --file <schema> [--paradigm relational|document|key-value|wide-column|graph] — paradigm-aware: ERD for relational, access-pattern map for document, key+GSI sketch for DynamoDB/KV, node/edge for graph:
    • Relational → erDiagram with tables, PKs/FKs, and cardinality.
    • Document → embedding/reference tree showing what is nested vs referenced.
    • Key-value → access-pattern / key-design sketch (partition + sort key).
    • Wide-column → table-per-query / partition-key layout.
    • Vector → collection + metric/dimension + metadata filter fields.
    • Time-series → hypertable / measurement + tags + retention.
    • Graph → node-and-edge sketch with relationship types.
  4. Offer an expandable technical layer below the plain description: exact column types, index definitions, constraint names, on-delete behavior — for the reader who wants the precise DDL.
  5. If the target is a finding id, explain what it checks, which score/axis it affects (design | performance | both), why it matters, and how to reproduce it (verification.reproduce).

Query / EXPLAIN-plan mode

Two additional inputs, both reusing the db-query-patterns (M13) reasoning:

  • --query "<SQL>" — given a raw SQL statement, explain in plain language why it would be slow and what fixes it: detect M13 shapes (SELECT *, structural N+1, OFFSET deep paging, non-SARGable predicates), then recommend the concrete index, keyset rewrite, or predicate change that lets an index be used. This is static reasoning over the query text — no live DB needed.
  • paste-an-EXPLAIN-plan — given a pasted EXPLAIN/EXPLAIN ANALYZE plan, read the plan nodes (seq scans, sort/hash spills, row estimate vs actual, nested-loop blowups) and explain which step dominates and what index/rewrite removes it, again via the M13 reasoning.
  • If the user wants a live plan generated for them (running EXPLAIN against their database) rather than pasting one, mark the request needs_api / Tier-2 and do not fabricate plan numbers — explain statically from the query text instead, or ask them to paste the plan.

Honesty

  • Describe only what is actually in the model. Never invent columns, relationships, row counts, or latency. If a relationship is implied but not enforced (e.g. a logical FK with no constraint), say so explicitly.
  • Respond in the user's language (EN/ES); --lang overrides.

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