菜单
Quick multi-LLM second opinion. Sends a single prompt to GPT, Gemini, or Grok with a role-based system prompt and returns structured feedback.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Voice & Presence standard for fine art photography content. Guards the sound of product descriptions, gallery text, artist statements, and collection narratives so they read as written by a photographer, not generated by a machine. For post-draft diagnostics, see voice-audit.
Post-draft diagnostic for photography content. Scans for machine tells, assesses authenticity risk, checks voice continuity against the photographer's voice standard. Fires before committing content changes. For during-writing standards, see like-a-human.
"Enforces atomic commits, checkpoint summaries, rate-limit recovery, and safe resume patterns. Writes session pulses + cognitive memory so interrupted sessions can restart cleanly."
Guides GA4 setup and conversion tracking for flickersofmajesty.com. Focuses on e-commerce metrics: product views, purchase intent, and print size preferences.
Deep audience personas for fine art photography buyers. Feeds product descriptions, gallery curation, and emotional-hook-test calibration.
Final typographic polish before publishing product and gallery pages. Checks curly quotes, em-dashes, alt text, price formatting, and visual consistency.
| name | consult |
| description | Quick multi-LLM second opinion. Sends a single prompt to GPT, Gemini, or Grok with a role-based system prompt and returns structured feedback. |
One model. One question. Structured feedback.
/consult <model> <role> "prompt text"
/consult gpt structure "Review this gallery page layout for logical flow"
/consult gemini expand "What photography metadata standards should we include?"
/consult grok challenge "This page follows conventional portfolio patterns. What's better?"
IMPORTANT: Execute these commands directly using the Bash tool. Do NOT check if files exist first — just run them.
bash /home/user/ken/orchestrator/bootstrap-env.sh 2>/dev/null; pip3 install -q -r /home/user/ken/orchestrator/requirements.txt 2>/dev/null && python3 /home/user/ken/orchestrator/consult.py <model> <role> "prompt text"
Output: JSON response to stdout with keys: analysis, proposed_update, risks, confidence
Usage stats: Printed to stderr (model, tokens, cost)
Only if the command fails with No such file or directory or ModuleNotFoundError, tell the user:
"The orchestrator backend isn't available. Make sure the ken repo is cloned to
/home/user/ken/and runpip3 install -r /home/user/ken/orchestrator/requirements.txt."
claims, verify them before incorporating.