Unverified50% confidenceFactExact time
The core usage of TokenPrune is to wrap tool functions with the @prune_tool decorator, which automatically analyzes the structure of the returned dictionary, strips null values, compresses repetitive key-value patterns, and converts list-type data into a compact table form.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/23/2026
First Seen
Valid until: 1/21/2027
Sources
Related Entities
Related Claims
UnverifiedLangChain's @tool decorator mechanism allows developers to declare any Python function as a tool callable by a large model, and the framework automatically extracts tool description information from the function signature and docstring.67% similarUnverifiedAnthropic's billing documentation states that what counts toward tokens includes not only user input but also tool definitions, tool use blocks, and tool result blocks, and additionally appends built-in tool use prompts.66% similarUnverified自定义工具(Custom Tool)可以将重复流程封装起来实现一键复用,绕过重复推理65% similarUnverifiedreMarkable将用户的每一笔以矢量化笔画数据存储,记录位置、笔尖压力、倾斜角度、移动速度等多维传感器信息64% similarVerifiedThe general principle for achieving cache hits is to keep the prefix of the request context as stable as possible, placing fixed content such as system prompts and tool definitions at the very front, with per-turn user input appended at the end.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1088006API
curl https://kongchang.com/api/v1/knowledge/claims/1088006MCP
get_claim(id=1088006)