Multi-Agent Parallel Review Pattern (2026-07-21)

Proven pattern for diagnosing complex technical issues: dispatch 5+ independent agents simultaneously with the same diagnostic brief, then consolidate findings into a ranked consensus.

When to Use

Complex artifact/quality issues where no single agent has the full answer
User reports "a LOT of artifacts" or "all kinds of inconsistencies" but can't pinpoint the cause
Need both technical review (model settings, workflow) AND community research (GitHub issues, Reddit, social media)

Pattern

1. Write a single diagnostic brief

Save to /tmp/<topic>-review.txt. Include:

Exact technical setup (model, settings, prompts, frame counts)
What the user is seeing (symptoms)
What to investigate (specific questions)
Web search mandate: "Use mcp_searxng_searxng_web_search for every claim and cite the source URL"

2. Dispatch all peers in parallel

Use terminal(background=true, notify_on_complete=true) for each:

Claude Opus (ask.sh on 10.0.0.28) — best for technical reasoning
Kimi K2.7 Code (kimi-c profile) — good for code-level analysis
Kimi K2.6 (kimi profile) — broad knowledge
MiniMax M3 (minimax profile) — alternative perspective
GLM-5.2 (glm profile) — alternative perspective
Deep research (research profile, 600 turns) — GitHub, Reddit, HuggingFace, social media

3. Consolidate findings

When all complete, build a ranked table:

CRITICAL: all agents agree
HIGH: 4-5 agents agree
MEDIUM: 2-3 agents agree
UNIQUE: single agent, high-impact

4. Apply fixes in order

Test after each fix. Start with zero-cost config changes before model downloads or frame regeneration.

Pitfalls

kimi-c may hit tool name issues — the SearXNG MCP tool uses double underscores (mcp__searxng__) but the prompt says single. kimi-c may burn turns trying to resolve this. Accept partial results.
MiniMax may produce truncated output — the process log may only show reasoning, not the final answer. Check the full log with process(action='log').
Deep research can't access X/Twitter or Discord — SearXNG returns empty for social media queries. Document as uncertainty, not failure.
Don't wait for all before acting — apply consensus fixes as soon as 3+ agents agree. The remaining peers add detail but shouldn't block progress.

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