Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/lollipopkit/cc-plugins/recursive-arenanpx skills add lollipopkit/cc-plugins --skill recursive-arenagit clone --depth 1 https://github.com/lollipopkit/cc-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.00399 |
| Opus 5 | $0.00020 | $0.00199 |
| Sonnet 5 | $0.00008 | $0.00080 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
recursive-arena scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Recursive-Arena
Use the orchestrator:
python3 "${CLAUDE_PLUGIN_ROOT}/skills/recursive-arena/scripts/recursive_arena.py".
How to run
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.
Iteration Loop
For each outer iteration:
- Run
multi-modelto generate a best candidate. - Use judge summaries as critique input.
- Refine the prompt with the current best answer.
- Keep the global best by score and continue.
Configuration
Reuses multi-model .env configuration:
ARENA_MODELSARENA_OPENAI_BASE_URLorARENA_PROVIDER_<NAME>_BASE_URL- Optional API keys (
ARENA_OPENAI_API_KEY,ARENA_PROVIDER_<NAME>_API_KEY)
Optional orchestration env:
RLM_ARENA_ARENA_ITERSdefault inner arena iterationsRLM_ARENA_MAX_JUDGESdefault judge cap
Output and Safety
- Final answer is the best outer-iteration result.
- When useful, show a compact evolution table:
iterationwinner_model_id(numeric ID only)avg_judge_scorerefinement_applied
- Never disclose provider/model names.
- Never print secrets from
.env.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 53 lines · 41 tokens per session scan A c91a396a1300
recursive-arena is a skill published in the GitHub repository lollipopkit/cc-plugins (7 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 399 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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