llm-council
Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.
70
85%
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.90). The skill explicitly spawns external model CLIs (codex/claude/gemini/opencode or arbitrary custom commands) and ingests their textual outputs into the planning and judging workflow (see scripts/llm_council.py run_planners/run_judge and the SKILL.md Workflow which collect, anonymize, randomize, judge, and merge planner outputs), so untrusted third‑party model responses can materially influence decisions and subsequent actions.
- Repository
- am-will/codex-skills
- Commit
9f954c3
- Audited
- Security analysis
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