---
name: logicprobe-datamodel
description: "Use when reviewing design docs, specs, plans or migrations claiming entities, fields, constraints, relationships, data invariants, or before/after data-model equivalence: schema changes, migration logic, or data guarantees ('all records must have X', 'no orphan rows', 'ids unique') want executable data-model verification (migration coverage, copy consistency, rollback symmetry, DD1-DD4 regression). State machines and protocols: logicprobe; diagrams: logicprobe-uml."
---

# Logic Probe Data

> **Successor: `dsh-model-everything`.** Its counterpart skill is `model-everything-datamodel`, over `model_datamodel_verify`. Load that one when both plugins are installed; this skill stays accurate for `logicprobe_datamodel_verify`.

An unverified data model fails later. Model the schema and the migration, run them, and it becomes clear. Check every data claim before you act on it.

## Methodology

### Phase 1: Enumerate Data Claims

Read the document fully. Extract every verifiable data-model claim:

- Entity/table/collection names and fields
- Field types, nullability, defaults, unique constraints
- Relationships / foreign keys / referential integrity
- Data invariants ("always", "never", "must", "guaranteed")
- Migration claims ("rename field", "drop column", "backfill", "non-breaking")
- Copy/migration mappings ("source.a → target.x")

### Phase 2: Verify Against the Model or Codebase

For each claim, run the relevant verification:

- **Entity/field names**: compare against actual schema, API contract, or code types
- **Constraints**: check declared `required`, `unique`, `nullable`, `min/max`, `enum`
- **Relationships**: check target entity/field exists and `onDelete` is coherent
- **Migration**: build BEFORE/AFTER DataModelV1 and check migration coverage

### Phase 2 Trigger: Escalate to Data Model Verification?

Escalate immediately if the document contains ANY of:

- Schema/migration changes: added/removed/renamed fields, entities, constraints
- Data invariants: "all rows must", "counts must match", "no orphans", "never null"
- Copy/migration mappings: source-to-target field maps
- Before/after data-model equivalence claims: "non-breaking", "behavior preserved"
- Refactoring that changes field types, nullability, uniqueness, or relationships

## Data Model Verification Pipeline

```text
Document claims → Extract DataModelV1 → Runtime check:
  ├── DSH + `logicprobe_datamodel_verify` tool available → build DataModelV1 → call tool → structured report
  └── No engine available → Manual Verification Mode (references/data-model-guide.md)

Refactoring variant:
  Extract BEFORE DataModelV1 + AFTER DataModelV1
    → Run pipeline on AFTER model (DS/DA checks)
    → Compare BEFORE vs AFTER (DD1-DD4)
    → Flag any invariant that held in BEFORE but fails in AFTER
```

The **DataModelV1 shape** is in [`references/data-model-schema.md`](references/data-model-schema.md): entities, fields, keys, relationships, invariants, boundary checks, and the optional before/mapping/copy/migration/backup blocks. Those field names are the tool contract. A hand-written model that disagrees with them is rejected, not guessed at.

## Checks

### DS — Data structure

| # | Check | Severity if Violated |
|:--:|-------|:---:|
| DS1 | Schema well-formedness | Error |
| DS2 | Required-field completeness | Error/Warning |
| DS3 | Relationship integrity | Error |
| DS4 | Type/nullability consistency | Error/Warning |

### DA — Data adversarial probes

| # | Check | Severity if Violated |
|:--:|-------|:---:|
| DA1 | Null/empty injection | Error |
| DA2 | Boundary blast | Warning |
| DA3 | Uniqueness violation | Error/Warning |
| DA4 | Referential integrity violation | Warning |
| DA5 | Migration coverage | Error |
| DA6 | Copy consistency | Error |
| DA7 | Rollback/backup symmetry | Warning |
| DA8 | Idempotent constraints | Error/Warning |
| DA9 | Data monotonic | Error/Warning |
| DA10 | Data sequence | Error |
| DA11 | Data leads-to | Error/Warning |
| DA12 | Data atomicity | Error/Warning |

### DD — Before/after data regression

| # | Check | Severity if Violated |
|:--:|-------|:---:|
| DD1 | Data behavior preservation | Error |
| DD2 | Data invariant continuity | Error |
| DD3 | Delta summary | Warning |
| DD4 | Breaking change regression | Error/Warning |

Every `#` in these tables is a report field, not a name. Write what the check found for the
reader (「回滚与备份不对称」), in their language; keep the id for a report field quoted
verbatim, a baseline diff or a test name. The full rule is under "Writing the Answer" in the
`logicprobe` skill.

## Extraction Rule

Before writing any verification code, output a data-model table:

```text
Entity   | Field      | Type    | Required | Unique | Nullable | Notes
---------|------------|---------|----------|--------|----------|-------
User     | id         | uuid    | yes      | yes    | no       | PK
User     | email      | string  | yes      | yes    | no       |
Order    | userId     | uuid    | yes      | no     | no       | FK -> User.id
```

Show this table to the user and ask for confirmation before generating the harness. The #1 failure mode is extracting the wrong data model.

**Exception**: If the runtime reports `logicprobe interaction=auto`, do NOT call `ask_user_question`. Instead: (a) cite evidence for every extracted entity/field/constraint, (b) round-trip the filled model back into a table and compare it with the extraction table, and (c) mark the report `UNCONFIRMED`.

## When NOT to Escalate

Skip data-model verification when:

- The document makes no data-behavioral claims (pure API listings, file paths, numeric constants)
- The change is purely cosmetic (display names, comments)
- The data model is trivial (single entity, no constraints, no migration)
- The claim is purely structural (file paths, type names) — Phase 2 grep verification is sufficient

## Non-Goals

- Not a SQL migration executor (Flyway/Liquibase/Atlas territory)
- Not a runtime data-quality platform (Great Expectations/Soda territory)
- Not a general array/object/file-content modeling engine
- Not a replacement for Atlas/Squawk/Buf/Oasdiff — it is the design-time plan verifier that sits before them
