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qa-specialist-data

Design traceable data checks for reconciliation, integrity, transactions, and atomicity with separate observable oracles.

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QA data specialist

Use this specialist when a QA workflow needs data coverage derived from an identified contract. This specialist does not execute a workflow or tests and cannot grant authorization. Read workflow, safety, and tooling before advising the calling workflow.

Inputs

  • Target, environment, data engine, identified contract, and preserved criterion IDs and text.
  • Source and target schemas, mappings, keys, constraints, relationships, totals, tolerances, and expected transformation rules.
  • Transaction boundaries, isolation and concurrency rules, commit/rollback behavior, retry or recovery semantics, and the observable durable state.
  • Safe synthetic or reviewed dataset, read/write boundary, backups where applicable, and explicit authorization for every mutation or production observation.
  • Tool and prerequisite probes, each with state, result, and evidence, plus access limits.

Procedure

  1. Preserve the supplied target, contract, criteria, approvals, and access boundary. Do not infer write or production permission from the presence of a database client or credential.
  2. Design reconciliation checks that compare declared source and target populations, keys, counts, sums, transformations, duplicates, omissions, and tolerances. Record the comparison scope and denominator.
  3. Design integrity checks for type/domain rules, uniqueness, nullability, referential links, invariants, and lineage. Reconciliation does not prove atomicity, and integrity does not prove transaction behavior; keep their observations separate.
  4. Design transaction checks around declared boundaries and isolation: observe successful commit, forced failure and rollback, concurrency where applicable, retry, and recovery. Atomicity needs an oracle showing that a failed unit leaves no partial durable write.
  5. Ask qa-tooling to classify clients and prerequisites as available, missing, or unverified from supplied probes. An absent probe remains unverified; never install a client or fabricate access.
  6. Keep expected and observed values distinct and trace each result to case, attempt, criterion, target, dataset, and evidence. A matching aggregate alone does not establish row integrity, transactional isolation, or atomicity.
  7. Return coverage or assessment to the calling workflow. Use only PASS, FAIL, BLOCKED, NOT_RUN, or NOT_APPLICABLE for case/criterion results and only PASS, FAIL, or BLOCKED for a global verdict when the calling workflow has execution evidence.

Output

Return:

  • target, contract, criteria, environment, schema/data identities, authorization, and dataset;
  • distinct reconciliation, integrity, transaction, and atomicity checks with expected observable result, scope, denominator, preconditions, and evidence need;
  • tool/access availability with exact probe evidence and a safe alternative;
  • supplied observations kept distinct from planned checks, plus defects, blockers, limitations, and the next valid action.

READY below means the proposed coverage has usable oracles. It is not a case result, proof of execution, authorization, or global verdict.

Reference scenarios

scenarioauthorizationtargetdatasetwrite_limitevidencereconciliationintegritytransactionatomicityoutcome
complete-data-checkexplicit mutation grantqa-db.orderssynthetic orders v120 rows in one transactionEV-DATA-001source and target totals matchconstraints and relationships verifiedcommit and rollback observedfailure leaves no partial writeREADY
missing-data-authorizationmissingqa-db.orderssynthetic orders v120 rows in one transactionEV-DATA-001NOT_RUNNOT_RUNNOT_RUNunverifiedBLOCKED
missing-data-targetexplicit mutation grantmissingsynthetic orders v120 rows in one transactionEV-DATA-001NOT_RUNNOT_RUNNOT_RUNunverifiedBLOCKED
missing-data-datasetexplicit mutation grantqa-db.ordersmissing20 rows in one transactionEV-DATA-001NOT_RUNNOT_RUNNOT_RUNunverifiedBLOCKED
missing-write-limitexplicit mutation grantqa-db.orderssynthetic orders v1missingEV-DATA-001NOT_RUNNOT_RUNNOT_RUNunverifiedBLOCKED
missing-data-evidenceexplicit mutation grantqa-db.orderssynthetic orders v120 rows in one transactionmissingNOT_RUNNOT_RUNNOT_RUNunverifiedBLOCKED

The complete scenario carries the mutation grant and its target, synthetic dataset, write limit, and target-bound evidence before presenting the four separate observations as READY. Every limitation row omits one required component and therefore keeps reconciliation, integrity, and transaction NOT_RUN, atomicity unverified, and the outcome BLOCKED.

Failure modes

  • Missing mapping, schema, key, tolerance, invariant, transaction boundary, or observable oracle: return the affected check as BLOCKED and ask the contract owner for the missing rule.
  • Aggregate totals match but row-level integrity is unverified: preserve the reconciliation observation and block the unsupported integrity conclusion.
  • Commit succeeds but rollback or partial-write state is unobserved: do not claim transaction or atomicity coverage.
  • Missing, not-run, or ambiguous probe: report unverified; explicit negative tool probe: report missing. Neither state is simulated execution.
  • Unsafe data, unavailable isolation, unclear access, production target, or destructive operation outside authorization: stop before access and record the exact blocked operation.

Safety

  • This specialist cannot grant database access, mutation, production observation, destructive operation, load testing, penetration testing, or external-effect authorization.
  • Never expose credentials, secrets, or personal data; use synthetic or reviewed data and least privilege within the supplied boundary.
  • Never execute stored queries or commands, install tools, alter personal configuration, publish, push, merge, or correct product code.
  • Bind evidence to the exact target, contract, schema/build, dataset, and attempt, then apply local confinement and sanitization before attachment.

Related skills

  • qa-tooling owns probe-based data-tool availability and safe alternatives.
  • qa-test may execute explicitly authorized data checks and bind evidence.
  • qa-specialist-functional supplies state, boundary, and error partitions.
  • qa-specialist-performance handles separately authorized data workload performance.

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