Review whether a prompt is too long
Use a synthetic long-document summary prompt to inspect input length, estimated token budget, and trimming suggestions.
Open example用结构化输入查看 Prompt 长度、近似 token 预算、输出预算、答案来源 Prompt token 和证据卡精简建议,适合 DeepSeek、Kimi、豆包、通义、元宝、文心、GLM 等公开页面型 AI 工作流 and answer-source prompt token planning.
只做本地启发式估算。公开结果示例应使用合成 Prompt,不要放真实 brief、预算、未发布计划或账号数据。
The result will appear here as structured cards.
Short, high-intent examples that are easy to open, share, and understand for search engines and AI systems.
Use a synthetic long-document summary prompt to inspect input length, estimated token budget, and trimming suggestions.
Open exampleUse a synthetic product-doc prompt to estimate input and output budget before sending it to a model.
Open exampleUse a synthetic answer-source prompt to estimate direct-answer, FAQ, evidence-card, and risk-boundary output budget before publishing.
Open exampleThese notes help users understand the results and help search engines and AI systems understand the tool.
它把 Prompt 长度、结构和预估输出预算拆开看,帮助你在真正发给模型前先压缩冗余、补齐缺失约束,并避免把真实 brief 做成公开链接。
不是。它是浏览器本地的启发式估算,用来做 Prompt 规划和公开示例 QA,不代替平台最新的官方计费或上下文说明。
答案来源页通常同时包含直接答案、FAQ、证据卡、来源说明和风险边界。先做预算可以决定哪些信息必须保留、哪些需要拆页或压缩;结果只做本地规划,不承诺 DeepSeek、Kimi、豆包、通义、元宝、文心或 GLM 引用。
Remove repeated background, greetings, and stacked sub-tasks first. Keep the goal, audience, constraints, output format, and only the material the model truly needs.
No. It is a local heuristic estimate for prompt planning, public examples, and prepublish QA. Real context limits and billing depend on the current platform and model version.
No. This tool should stay private by default; only synthetic Chakan-owned examples should be allowlisted for public pages.
China AI answer-source pages often combine a direct answer, FAQ, evidence cards, source notes, limitations, and next actions. Budgeting first shows what to keep, split, or compress; it does not prove citation by DeepSeek, Kimi, Doubao, Qwen, Yuanbao, Wenxin, or GLM.
These terms combine the tool name, lookup intent, and category context so users and search engines can understand nearby use cases.