review-correctness-query-planner-execution

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Use when reviewing pull requests for query semantics, planner/optimizer correctness, execution-engine behavior, and behavior-preservation regression risks before merge.

D3Hunter By D3Hunter schedule Updated 5/29/2026

name: review-correctness-query-planner-execution description: Use when reviewing pull requests for query semantics, planner/optimizer correctness, execution-engine behavior, and behavior-preservation regression risks before merge.

Review Correctness: Query, Planner, and Execution

Overview

Use this skill to identify behavioral correctness issues in query/planner/execution changes. Focus on domain behavior, control-flow semantics, SQL/parser/binder/planner/executor correctness, and behavior-preservation regressions.

This skill covers correctness discovery only. After findings are identified, hand off output rendering to review-output-format.

This is a static-analysis-first review flow. Do not run build/test commands directly as part of this skill.

Input

This skill accepts exactly three input parameters:

  • code_path (required): absolute path to the cloned codebase; this is the working directory for review.
  • diff_filename (required): filename of the diff to review.
  • output_filename (required): final output JSON filename for the rendered findings payload.

Output

  • Final output must be a file named exactly as output_filename.
  • File content format is already defined by review-output-format.
  • Do not invent or emit an alternate output schema.

Review Flow

  1. Scope behavioral correctness surface

    • Use code_path as the working directory.
    • Load and review changes from diff_filename as the primary review scope.
    • Identify changed behavioral boundaries: domain logic, control flow, input/output contracts, parser/binder/planner logic, and execution operators.
    • Expand each touched behavior block beyond the hunk before concluding:
      • open the full changed function body
      • open all callers and all callees when they participate in state/token/operator handoff
      • include unchanged branches that share state flags, offsets, or fallback paths
  2. Run full checklist pass

  3. Run high-risk trigger gate for parser/scanner and reverse/forward scan paths

    • Activate this gate when any changed path touches tokenization/framing/splitting/chunked reads/reverse scans/fallback parsing/state flags.
    • Mandatory boundary matrix in this gate:
      • framing token: delimiter-only ("") vs non-empty content
      • carry state: pending/partial block empty vs non-empty
      • scan direction/path: reverse vs forward (or equivalent alternate reader paths)
    • Include at least one adversarial scenario where a chunk ends exactly at the delimiter and the next chunk continues the same logical record.
    • Verify framing artifacts cannot be promoted into record content while a partial block is in progress.
    • Verify fallback/error branches do not reset state flags on framing-only artifacts.
  4. Build cross-function traces for changed behavioral boundaries

    • For parser/scanner/token-stream changes: trace at least one end-to-end record path from producer to consumer, including boundary tokens ("", delimiter-only, partial records across chunks/files).
    • For planner/rewrite/pushdown changes: trace at least one end-to-end operator path and verify early-return branches preserve required operators instead of silently dropping them.
    • Capture concrete handoff assumptions between functions (for example: token shape, ordering, offset semantics, state-flag transitions).
    • Keep an internal trace table with at least:
      • one normal-path row
      • one boundary-path row
      • state snapshots before/after each handoff (pending, flags, offsets, output emission decision)
  5. Evaluate each potential issue with evidence

    • Confirm at least one objective signal:
      • code-path contradiction with requirements/invariants
      • semantic mismatch between query stages or execution paths
      • boundary/edge-case handling gap
      • concrete behavior regression scenario
      • trace-table state contradiction (for example: framing artifact changes semantic state)
    • If evidence is weak, request targeted validation instead of asserting a defect.
  6. Assign severity for handoff

    • Blocker: likely incorrect results, semantic corruption, or major contract break.
    • Major: high-confidence correctness risk with meaningful user or operational impact.
    • Minor: localized correctness gap with limited blast radius.
    • Info / Nit: low-risk observation, clarification, or polish.
  7. Prepare findings payload

    • One issue per finding.
    • Capture: severity, title, why, scope, risk_if_unchanged, evidence, change_request.
    • Keep scope concrete (path:line, module, branch, or scenario boundary).
  8. Required output handoff

    • After the correctness pass is complete, invoke review-output-format.
    • Render final findings strictly with that skill's output contract.
    • Write that JSON to output_filename.

Runtime Validation Policy

  • Never execute project build commands during this review flow.
  • Never execute project test commands during this review flow.
  • Never run broad verification tasks (full suite, integration matrix, benchmarks) directly in this skill.
  • If runtime confirmation is needed, request targeted validation with the minimal scenario and exact command, but do not run it yourself.
  • Keep review latency low by relying on diff evidence, invariants, and local code-path reasoning.

Review Depth Rules

  • Do not emit a no-findings conclusion until every checklist section is passed or explicitly N/A.
  • Prioritize behavioral correctness risk over style/structure feedback.
  • For non-trivial findings, include at least one concrete scenario (input/condition -> incorrect outcome).
  • For token/streaming/reverse-scan diffs, do not conclude until chunk/file boundary matrix checks are explicitly completed.
  • For pushdown/rewrite diffs, do not conclude until operator-preservation checks (including early-return branches) are explicitly completed.
  • For parser/scanner tokenization changes, do not conclude until unchanged neighboring fallback/state-transition branches are inspected.
  • No-findings output is forbidden when the internal boundary trace table is missing or incomplete.
  • If uncertain, ask for focused tests/validation rather than making a hard claim.

References

Install via CLI
npx skills add https://github.com/D3Hunter/ai-engineer --skill review-correctness-query-planner-execution
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