Arena Council — Multi-Model AI Debate
AdvisoryAudited by Static analysis on May 3, 2026.
Overview
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Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Your request may be transformed into a jailbreak-style prompt without an explicit confirmation each time, potentially producing outputs you did not intend to solicit.
The skill can automatically rewrite the user's prompt using a stored bypass technique when a model is marked censored, changing the prompt semantics and attempting to override model refusals.
If model is known-censored, wrap prompt with the stored technique... return apply_technique(prompt, technique)
Make any refusal-bypass behavior explicit, disabled by default, and require a clear user opt-in before modifying prompts.
Prompts given to this skill may be sent to multiple locally running models rather than just one model.
The skill sends prompts to a local LM Studio chat-completions API, which is expected for a local multi-model council but is still a real model-invocation data flow.
LMSTUDIO_BASE = "http://127.0.0.1:1234/v1" ... session.post(f"{LMSTUDIO_BASE}/chat/completions", json=payloadUse explicit model lists and avoid submitting sensitive prompts unless you are comfortable with all selected local models receiving them.
If a god-mode folder exists, this skill may execute additional Python code that was not included in this review and may change how prompts are handled.
The skill conditionally adds a sibling god-mode scripts directory to Python's import path and imports modules from it, so runtime behavior depends on unbundled code outside this skill's reviewed files.
GOD_MODE_DIR = Path(__file__).parent.parent.parent / "god-mode" / "scripts" ... sys.path.insert(0, str(GOD_MODE_DIR))
Declare this dependency clearly, pin or bundle reviewed helper code, and avoid importing executable code from sibling skill directories by default.
A saved profile can affect later sessions, causing future prompts to be modified based on prior or potentially altered profile state.
The skill stores and later reuses persistent model-profile data that determines whether and how future prompts are wrapped with god-mode techniques.
profiles_file = GOD_MODE_DIR / "model_profiles.json" ... profiles[model_id] = result ... save_profiles(profiles)
Store profiles in a clearly scoped location, show users when profile state is used, provide a disable/clear option, and validate profile contents before applying prompt transformations.