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From recursive-reasoning
Orchestrates recursive outer-loop refinement with multi-model arena battles each round to iteratively improve task outputs. Use for recursive arena, multi-LLM consensus with refinement, or model-battle workflows.
How this skill is triggered — by the user, by Claude, or both
Slash command
/recursive-reasoning:recursive-arenaThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use the orchestrator:
Use the orchestrator:
python3 "${CLAUDE_PLUGIN_ROOT}/skills/recursive-arena/scripts/recursive_arena.py".
python3 "${CLAUDE_PLUGIN_ROOT}/skills/recursive-arena/scripts/recursive_arena.py" \
--prompt "<task>" --iters 4 --arena-iters 3 --json
Common flags: --max-judges, --temperature, --max-tokens, --timeout.
For each outer iteration:
multi-model to generate a best candidate.Reuses multi-model .env configuration:
ARENA_MODELSARENA_OPENAI_BASE_URL or ARENA_PROVIDER_<NAME>_BASE_URLARENA_OPENAI_API_KEY, ARENA_PROVIDER_<NAME>_API_KEY)Optional orchestration env:
RLM_ARENA_ARENA_ITERS default inner arena iterationsRLM_ARENA_MAX_JUDGES default judge capiterationwinner_model_id (numeric ID only)avg_judge_scorerefinement_applied.env.npx claudepluginhub lollipopkit/cc-plugins --plugin recursive-reasoningOrchestrates parallel analysis of coding problems across AI models (Claude, GPT, Gemini, Grok) via CLI tools or APIs, collects recommendations, and synthesizes optimal solution.
Optimizes the harness code around a fixed base model (memory, retrieval, prompts, tool selection) via evolutionary Pareto search using native Agent/Workflow tools instead of a standalone Python driver.
Runs 3 AI models in parallel (gpt-5.2-pro, gemini-3-pro-preview, claude-opus-4-5-20251101) for diverse perspectives on code queries. Invoke via /ask-council or auto-activates.