[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71DKC0WYXMBTT6Q64EPK7M9":3,"skill-same:01M71DKC0WYXMBTT6Q64EPK7M9":52},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":26,"linkOnly":27,"markdownContent":28,"markdownBody":29,"frontMatter":30,"refName":32,"commitSha":33,"skillDirectory":34,"forksCount":35,"repositoryHtmlUrl":36,"repositoryHomepageUrl":6,"ownerHtmlUrl":37,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":38,"install":39,"resources":51},"01M71DKC0WYXMBTT6Q64EPK7M9","mm:consult",null,"Asks other LLMs through OpenRouter with Mirror context","mirror-mind-ai\u002Fmirror","mirror-mind-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F284655986?v=4","01M71DK28AKP6F5W1QCCBXN1W2","01M71DK29N7M7PSY7645ZQZ2B3",21,"MIT","https:\u002F\u002Fgithub.com\u002Fmirror-mind-ai\u002Fmirror\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fmm-consult\u002FSKILL.md",[],[18,5,19,20,21,22,23,24,25],"mm","consult","with","llms","true","openrouter","mirror","context","2026-11-10 10:12:30",false,"---\nname: \"mm:consult\"\ndescription: Asks other LLMs through OpenRouter with Mirror context\nuser-invocable: true\n---\n\n# Consult\n\nSends prompts with Mirror identity context to other models through OpenRouter.\n\n## Syntax\n\n```\n\u002Fmm:consult \u003Cfamily> [tier] [\"question\"]\n\u002Fmm:consult credits\n```\n\n- **family:** `gemini`, `grok`, `deepseek`, `openai`, `claude`, `llama`, or a direct model ID such as `google\u002Fgemini-2.5-pro`\n- **tier:** `lite` (default), `mid`, `flagship`\n- **question present:** send it directly\n- **question missing:** synthesize the current conversation and create the prompt\n\n## Flow\n\n> The model call answers from TypeScript, bounded by the extraction timeout (`MEMORY_LLM_TIMEOUT_EXTRACTION`, 60 s) with bounded retries. (The 10-minute ceiling CR072 added applied only to the Python engine, which is gone.)\n\n### Explicit Question\n\nAnalyze the message to determine persona and journey using the same Mirror routing.\n\n```bash\nmirror consult FAMILY TIER \"QUESTION\" \\\n  [--persona PERSONA] [--journey JOURNEY] [--org]\n```\n\n**Examples:**\n- `\u002Fmm:consult gemini lite \"draft an opening for this article\"` -> `mirror consult gemini lite \"draft an opening for this article\" --persona writer`\n- `\u002Fmm:consult deepseek \"is this design overengineered?\"` -> `mirror consult deepseek \"is this design overengineered?\" --persona engineer`\n\nThe script prints the response, cost, and balance. Always show the complete response to the user without summarizing or omitting it. Any Claude comments come after the full response.\n\n### No Question\n\nWhen the user omits the question, they want a second opinion on the current conversation. Synthesize only Mirror Mode content: reflection, strategy, and content. Ignore Builder Mode content such as code, debugging, and project architecture.\n\n1. Synthesize the context into a self-contained prompt: topic, goal, relevant journey\u002Fattachments\u002Freferences, what was discussed or decided, and what the user is asking now.\n2. Formulate a clear request for the external LLM.\n3. Send it as an ask:\n\n```bash\nmirror consult FAMILY TIER \"SYNTHESIZED_PROMPT\" \\\n  [--persona PERSONA] [--journey JOURNEY] [--org]\n```\n\nThe synthesized prompt must be self-contained. The external LLM has no access to the conversation, so include concrete details instead of vague references like \"as discussed.\"\n\nExample prompt:\n\n```\nI am preparing episode 5 of the Reflexo series, about leadership and complexity.\nThe episode covers [key script points]. I have already suggested topics A, B, and C.\n\nSuggest 3 alternative article topics for software leaders, keeping depth without academicism.\n```\n\n## Credits\n\n```bash\nmirror consult credits\n```\n\nShows OpenRouter usage and remaining balance.\n\n## Available Families And Tiers\n\n| Family | Lite | Mid | Flagship |\n|---------|------|-----|----------|\n| gemini | gemini-2.5-flash-lite | gemini-2.5-flash | gemini-2.5-pro |\n| grok | grok-3-mini | grok-3 | grok-4.1-fast |\n| deepseek | deepseek-chat | deepseek-v3.2 | deepseek-r1 |\n| openai | gpt-5.4-nano | gpt-5.4-mini | gpt-5.4 |\n| claude | haiku-4.5 | sonnet-4.6 | opus-4.6 |\n| llama | llama-3.3-70b-instruct | llama-4-scout | llama-4-maverick |\n","# Consult\n\nSends prompts with Mirror identity context to other models through OpenRouter.\n\n## Syntax\n\n```\n\u002Fmm:consult \u003Cfamily> [tier] [\"question\"]\n\u002Fmm:consult credits\n```\n\n- **family:** `gemini`, `grok`, `deepseek`, `openai`, `claude`, `llama`, or a direct model ID such as `google\u002Fgemini-2.5-pro`\n- **tier:** `lite` (default), `mid`, `flagship`\n- **question present:** send it directly\n- **question missing:** synthesize the current conversation and create the prompt\n\n## Flow\n\n> The model call answers from TypeScript, bounded by the extraction timeout (`MEMORY_LLM_TIMEOUT_EXTRACTION`, 60 s) with bounded retries. (The 10-minute ceiling CR072 added applied only to the Python engine, which is gone.)\n\n### Explicit Question\n\nAnalyze the message to determine persona and journey using the same Mirror routing.\n\n```bash\nmirror consult FAMILY TIER \"QUESTION\" \\\n  [--persona PERSONA] [--journey JOURNEY] [--org]\n```\n\n**Examples:**\n- `\u002Fmm:consult gemini lite \"draft an opening for this article\"` -> `mirror consult gemini lite \"draft an opening for this article\" --persona writer`\n- `\u002Fmm:consult deepseek \"is this design overengineered?\"` -> `mirror consult deepseek \"is this design overengineered?\" --persona engineer`\n\nThe script prints the response, cost, and balance. Always show the complete response to the user without summarizing or omitting it. Any Claude comments come after the full response.\n\n### No Question\n\nWhen the user omits the question, they want a second opinion on the current conversation. Synthesize only Mirror Mode content: reflection, strategy, and content. Ignore Builder Mode content such as code, debugging, and project architecture.\n\n1. Synthesize the context into a self-contained prompt: topic, goal, relevant journey\u002Fattachments\u002Freferences, what was discussed or decided, and what the user is asking now.\n2. Formulate a clear request for the external LLM.\n3. Send it as an ask:\n\n```bash\nmirror consult FAMILY TIER \"SYNTHESIZED_PROMPT\" \\\n  [--persona PERSONA] [--journey JOURNEY] [--org]\n```\n\nThe synthesized prompt must be self-contained. The external LLM has no access to the conversation, so include concrete details instead of vague references like \"as discussed.\"\n\nExample prompt:\n\n```\nI am preparing episode 5 of the Reflexo series, about leadership and complexity.\nThe episode covers [key script points]. 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