원클릭으로
ase-meta-quorum
Query Multiple AIs for Quorum Answer.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Query Multiple AIs for Quorum Answer.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Query foreign LLM for chat. Use this skill if a foreign LLM like OpenAI ChatGPT, Google Gemini, DeepSeek or xAI Grok should be queried with a single chat message.
Use when turning a memory-corruption bug into a working PoC — stack/ROP, glibc heap & FSOP, format strings, browser/JIT type confusion & UAF, Linux/Windows kernel LPE against ASLR/DEP/CFG/CET/V8-Sandbox
Tinder for your Claude Code skills. Reviews a sorted deck of every installed skill and lets you swipe keep / delete / skip on each one. Use when the user wants to bulk-clean their skill collection, triage unused skills, or do interactive skill cleanup.
Use when the user wants to report a bug, file an issue, submit a bug report, or report any problem with the mobile-app plugin.
Resolve PR review feedback. Use when addressing review comments, resolving review threads, or fixing code-review feedback.
扫描本机 Claude Code 和 Codex 的会话日志,统计哪些 skill 有本地调用证据、哪些在本机无证据(已安装但日志无痕迹,不等于从未使用)、调用排行、月度趋势、项目分布,输出终端表格和 Markdown 报告,可导出 CSV/JSON。Use when the user asks to 统计 skill 使用, 看 skill usage, find zombie skills, 僵尸 skill, which skills are installed but never used, skill 调用排行, skill usage report, skill 使用健康度, audit personal skill arsenal, or manage which skills to keep or remove.
| name | ase-meta-quorum |
| argument-hint | [--help|-h] [--models|-m <model>[,...]] <question> |
| description | Query Multiple AIs for Quorum Answer. |
| user-invocable | true |
| disable-model-invocation | false |
| effort | high |
| allowed-tools | ["Agent","TaskCreate"] |
@${CLAUDE_SKILL_DIR}/../../meta/ase-control.md @${CLAUDE_SKILL_DIR}/../../meta/ase-skill.md @${CLAUDE_SKILL_DIR}/../../meta/ase-getopt.md
Query Multiple AIs for Quorum Answer$ARGUMENTS
Find a *quorum answer* on an arbitrary question, by querying *multiple* AIs for an *optimal consensus*.Prepare the LLM query by setting to the following