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Loop Review

Iterative plan quality assurance. Spawns dual parallel reviewer subagents — one checking intent coverage against user's original ask, one checking standalone quality — and loops until the plan passes both or hits max iterations.

When to Use

• After saurun:writing-plans (or any planning skill) completes
• When you want automated QA before executing a plan
• When plan quality matters (complex features, multi-task plans)
• /loop-review with optional plan file path

When NOT to Use

• Plan is a simple 1-2 task change (overhead not worth it)
• You just need coverage verification against a spec (use saurun:verify-plan-coverage)
• Plan is already being executed (review first, execute after)

Phase 0: Context Detection

Resolve Plan Path

1. If $ARGUMENTS contains a file path → use it
2. Otherwise → find most recent .md in _docs/plans/ by modification time (use Glob)
3. If no plan found → AskUserQuestion: "Which plan file should I review?"

Read the plan file. Store contents as PLAN_CONTENT.

Extract User's Original Ask

Search conversation history for the user's original request that led to plan creation. Look for:

• The first substantive user message before planning began
• Messages containing requirements, feature requests, or problem descriptions
• Ignore meta-messages like "use writing-plans" or "create a plan"

Store verbatim as USER_ORIGINAL_ASK.

Fallback: If no clear original ask found in conversation history → AskUserQuestion: "What was the original request or goal this plan should fulfill? (paste verbatim or summarize)"

Reviewer Dispatch

Both reviewers are dispatched via Task(subagent_type="general-purpose"). Each gets a prompt template with placeholders replaced before dispatch.

Prompt templates:

• Intent reviewer: Read intent-reviewer-prompt.md from this skill directory, replace all placeholders
• Quality reviewer: Read quality-reviewer-prompt.md from this skill directory, replace all placeholders

Dispatch rules:

• All active reviewers spawned in a single message (parallel Task calls)
• subagent_type: "general-purpose"
• No model override (inherits session model)

Main Loop

intent_passed = false
quality_passed = false
iteration = 1
MAX_ITERATIONS = 3

WHILE iteration <= MAX_ITERATIONS AND (NOT intent_passed OR NOT quality_passed):

  # 1. Build reviewer list (skip already-passed reviewers)
  reviewers = []
  IF NOT intent_passed: reviewers.add(INTENT)
  IF NOT quality_passed: reviewers.add(QUALITY)

  # 2. Read prompt templates, replace placeholders
  For each reviewer:
    Read template file from this skill directory
    Replace {{PLAN_CONTENT}}, {{PLAN_PATH}}, {{ITERATION}}, {{MAX_ITERATIONS}}
    For intent reviewer only: replace {{USER_ORIGINAL_ASK}}

  # 3. Spawn reviewers in parallel (ALL Task calls in single message)
  Dispatch all reviewers as Task(subagent_type="general-purpose")

  # 4. Parse results
  For each reviewer result:
    Parse VERDICT line: ACCEPT, REVISE, or ABORT
    IF ACCEPT → mark that reviewer as passed
    IF ABORT → stop loop immediately, report to user, ask for guidance

  # 5. Collect issues
  Merge all ISSUES from non-passed reviewers into single list
  IF no issues remain → ACCEPT. Report success to user. Done.

  # 6. Apply fixes (priority order)
  Sort issues: HIGH intent → HIGH quality → MEDIUM intent → MEDIUM quality
  For each HIGH and MEDIUM issue:
    Apply fix to plan file using Edit tool
    Skip LOW issues (informational only)

  # 7. Re-read plan after edits
  PLAN_CONTENT = Read(plan_path)
  iteration++

# Loop exit
IF iteration > MAX_ITERATIONS AND NOT (intent_passed AND quality_passed):
  Show remaining issues to user
  AskUserQuestion: "Max iterations reached. How would you like to proceed?"
    Options:
    - "Accept plan as-is with known issues"
    - "Fix remaining issues manually and re-run"
    - "Continue for N more iterations"
ELSE:
  Report: "Plan accepted after {iteration} iteration(s). Both reviewers passed."

Shared Output Format

Both reviewer prompts include this core format (intent reviewer adds additional sections before DIMENSION_SCORES):

VERDICT: ACCEPT | REVISE | ABORT
OVERALL_SCORE: N/10
ITERATION: N/M

DIMENSION_SCORES:
| Dimension | Score | Weight | Notes |
|-----------|-------|--------|-------|
| ... | N/10 | Nx | ... |

ISSUES:
| # | Severity | Dimension | Location | Issue | Suggested Fix |
|---|----------|-----------|----------|-------|---------------|
| 1 | HIGH | ... | Task N / Section X | ... | ... |

SUMMARY:
[2-3 sentence narrative of findings]

Parsing rules:

• VERDICT line determines pass/fail/abort
• ISSUES table provides fix instructions for Edit tool
• OVERALL_SCORE is informational (verdict is authoritative)
• If output doesn't match format, treat as REVISE with a note about unparseable output

Accept Criteria

A reviewer returns ACCEPT when:

• OVERALL_SCORE >= 9, OR
• Zero HIGH or MEDIUM issues found

Both reviewers must ACCEPT for the plan to pass the loop.

Common Mistakes

Red Flags — Rationalization Table