By mistakeknot
Cross-AI peer review — quick (Claude↔Codex), deep (Oracle), council (multi-model), mine (disagreement extraction).
Cross-AI peer review for Claude Code.
Single-model review catches a lot, but models have blind spots: and they tend to have the same blind spots consistently. interpeer sends your code or documents to a different model for a second opinion, with four escalation modes depending on how much scrutiny you need.
Quick (qinterpeer): sends to Codex CLI for fast Claude↔GPT feedback. Takes seconds, catches surface-level disagreements.
Deep (interpeer): sends to Oracle (ChatGPT 5.2 Pro) with prompt optimization and large context support (~200k tokens). Takes minutes, catches architectural and design issues.
Council (winterpeer): full LLM Council with multi-model consensus. Slow, but useful for critical decisions where you want genuine multi-perspective analysis.
Mine (splinterpeer): the interesting one. Instead of just getting a second opinion, this mode extracts the disagreements between models and converts them into actionable artifacts: tests for disputed behavior, specs for ambiguous requirements, and questions for genuinely unclear design choices. Models disagree about interesting things.
First, add the interagency marketplace (one-time setup):
/plugin marketplace add mistakeknot/interagency-marketplace
Then install the plugin:
/plugin install interpeer
Requires Codex CLI for quick mode and Oracle CLI for deep mode.
/interpeer
Auto-detects which AI tools are available and offers the appropriate modes.
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npx claudepluginhub mistakeknot/interagency-marketplace --plugin interpeer[DEPRECATED — use intervoice] Analyze your writing style and adapt Claude's output to sound like you. Replaced by intervoice, which reads one global multi-register profile instead of per-project glob-routed files.
Recursive AGENTS.md generator with integrated Oracle critique, CLAUDE.md harmonization, incremental updates, diff previews, and smart monorepo scoping. Cross-AI compatible.
Token-efficient code reconnaissance for LLMs. Autonomous skills save 48-85% tokens via diff-context, semantic search, structural patterns, and symbol analysis. Includes MCP server for direct tool integration.
Self-improving agent rig: codifies product and engineering discipline into composable workflows from brainstorm to ship. Compounds knowledge, generates domain agents, monitors its own docs, and surfaces conservative update drift. Orchestrates Claude, Codex, and Oracle through 6 agents, 52 commands, 19 skills, 0 MCP servers. Factory substrate: CXDB turn DAG, scenario bank with satisfaction scoring, evidence pipeline, agent capability policies. Companions: interspect, interphase, interline, interflux, interpath, interwatch, interslack, interform, intercraft, interdev, interpeer, intertest.
Token efficiency benchmarking, session analytics, and API-equivalent cost analysis for agent workflows
Configurable multi-model code review, plan review, and general review with consensus convergence
Symmetric two-AI peer review using OpenAI Codex CLI. Both AIs review independently in a blind pass, then debate per-issue with terminal states until convergence. Catches significantly more issues than single-pass validation.
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Multi-agent adversarial review panel — 4-6 AI reviewers debate your code/plans, then a judge delivers a structured verdict with epistemic labels. Bundles plan-review-integrator for applying review findings back into implementation plans.
Multi-agent deliberation for AI coding assistants
Use when you want a delegated second opinion or implementation from GPT (Codex), Gemini, Grok (xAI), or OpenRouter (config-driven, 400+ models) - seven expert subagents (Architect, Plan Reviewer, Scope Analyst, Code Reviewer, Security Analyst, Researcher, Debugger) and bundled ask-gpt/ask-gemini/ask-grok/ask-openrouter/ask-all/consensus commands, advisory (read-only) or implementation (write; Grok and OpenRouter are advisory-only).