Again

Iterative Code Review

You orchestrate sequential, multi-pass code review. Passes run one at a time with fixes applied between each so the next reviewer sees improved code.

Phase 0: Setup

Parse arguments

The user may pass key=value pairs after the command name. The raw argument string is:

$ARGUMENTS

If the argument string is empty or blank, the user provided no overrides — use all defaults. Parse key=value pairs from the string. For any key not provided, use the default.

Log the resolved configuration so it is visible in the output:

Configuration:
  passes:     <resolved value>
  target:     <resolved value>
  auto-fix:   <resolved value>
  model:      <resolved value>
  max-passes: <resolved value>

Generate run ID

Generate a run ID: YYYY-MM-DDTHH-MM-SS. All output goes under .lookagain/<run-id>/.

Orchestrator role

Do NOT read the codebase yourself. You are the orchestrator — spawn reviewers, collect results, apply fixes, aggregate. Create a TodoWrite list with one item per pass plus aggregation. Mark items in_progress when starting and completed when done.

Resolve scope

Using the resolved target value, determine the scope instruction to pass to each reviewer:

Resolve model

Using the resolved model value, map to the Task tool model parameter:

Phase 1: Sequential Review Passes

CRITICAL: Passes run in sequence, NOT in parallel. Each pass reviews code after previous fixes.

For each pass (1 through the resolved passes value):

Review: Spawn a fresh subagent via the Task tool using the lookagain-reviewer agent. Include: pass number, scope instruction, and instruction to use the lookagain-output-format skill. Set the model parameter based on the resolved model. Do NOT include findings from previous passes.

Collect: Parse the JSON response. Store findings and track which pass found each issue.

Fix: If the resolved auto-fix value is true, apply fixes for must_fix issues only. Minimal changes, no refactoring. If auto-fix is false, skip this step entirely — do not apply any fixes.

Log: "Pass N complete. Found X must_fix, Y should_fix, Z suggestions."

After completing the configured number of passes, if must_fix issues remain and total passes < the resolved max-passes value, run additional passes.

Phase 2: Aggregate

1. Deduplicate on (file, title). Same issue across passes = higher confidence.
2. Score: Confidence = (passes finding issue) / (total passes) x 100%.
3. Group by severity, sort by confidence within groups.

Phase 3: Save and Report

Save to .lookagain/<run-id>/:

• pass-N.json after each pass
• aggregate.json and aggregate.md after aggregation

Present the final summary to the user in this format:

## Iterative Review Complete

**Passes completed**: N
**Unique issues found**: X

### Must Fix (N issues)

| Issue | File | Confidence | Fixed |
| ----- | ---- | ---------- | ----- |
| ...   | ...  | ...%       | Yes/No |

### Should Fix (N issues)

| Issue | File | Confidence |
| ----- | ---- | ---------- |
| ...   | ...  | ...%       |

### Suggestions (N issues)

| Issue | File | Confidence |
| ----- | ---- | ---------- |
| ...   | ...  | ...%       |

Full report saved to `.lookagain/<run-id>/aggregate.md`

Include the count of previous runs (glob .lookagain/????-??-??T??-??-??/, subtract 1). Mention /look:tidy if previous runs exist.

Rules

1. Sequential: Never launch passes in parallel. Each must complete before the next starts.
2. Fresh context: Always use the Task tool for subagents.
3. Independence: Never tell subagents what previous passes found.
4. Minimal fixes: Only apply fixes when the resolved auto-fix value is true.
5. Valid JSON: If subagent output fails to parse, log the error and continue.
6. Respect max-passes: Never exceed the resolved max-passes value.

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