Trace LiteLLM agents with Maple: export LiteLLM's v2 OpenTelemetry spans (Python SDK or self-hosted LiteLLM Proxy) plus your own agent/tool spans so each conversation is one Maple Agent Session with transcript, tool calls, tokens and cost. Triggers on 'trace my litellm agent', 'add Maple to litellm', 'agent sessions for litellm', 'OpenTelemetry for litellm', 'trace the litellm proxy'.
这个条目提供什么？
maple-agent-tracing-litellm 是 ChatHome Skills 收录的 技能 条目，来源为 GitHub Skill Search，质量分 48/100。 # Maple agent tracing: LiteLLM Goal: every conversation = one Maple Agent Session. Each agent run = one turn (one trace) with transcript, LiteLLM `chat <model>`. 作为 agent 技能，它把一组可复用的任务指令打包成 Codex 和 Claude Code 等 AI 编程 agent 可直接加载的格式，无需为该任务手写胶水代码。 该条目由 ChatHome Skills 的每日抓取从官方 registry 和 GitHub 发现查询中收录，每次运行都会重新核验仓库事实、新鲜度信号和安装元数据。 质量分综合了官方 registry 收录情况、可用安装命令、许可证完整性、仓库活跃度和 GitHub star 趋势，完整算法说明见来源页。安装命令已列于上方，可直接复制使用。 在将 maple-agent-tracing-litellm 加入生产 agent 工作流前，请核对上方的最近更新日期和仓库状态——下方事实快照是最近一次抓取的时点值。
# Maple agent tracing: LiteLLM Goal: every conversation = one Maple Agent Session. Each agent run = one turn (one trace) with transcript, LiteLLM `chat <model>` spans with tokens,
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.