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 exampleUse this ai prompt token budget estimator tool to inspect, convert, or generate a clear result directly in your browser.
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 exampleUse a synthetic prepublish review prompt to trim direct answers, source notes, FAQs, evidence cards, and next-step tools into a publishable budget.
Open exampleThese notes help users understand the results and help search engines and AI systems understand the tool.
It helps you inspect or process this value and get a readable result quickly.
Local tools run in the browser when possible. Server-side checks only use the input needed to complete the lookup.
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.
Repeated direct-answer copy, long source notes, FAQ sections that turn into mini tutorials, and evidence cards mixed with next-step tools are the usual causes. Keep the main answer, source boundary, evidence-card labels, and the next action first, then compress the rest.
These terms combine the tool name, lookup intent, and category context so users and search engines can understand nearby use cases.