A collection of agent trajectory analysis techniques and benchmark
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Updated
Aug 4, 2026
A collection of agent trajectory analysis techniques and benchmark
DeepSeek Harness 的执行迷宫——看 Agent 真实怎么干活:迷宫时间轴 · 数据轨道 · 确定性执行分析 · 多会话对比 | The execution maze for DSH agents: maze timeline, per-step data tracks, deterministic execution analysis, multi-session comparison. Formerly dsh-trace-compare.
Train a JEPA world model on a set of pre-collected trajectories from an environment involving an agent in two rooms.
A compiler infrastructure for agentic trajectories — the LLVM for agent traces.
Visualize ATIF trajectory in VSCode
VCR cassettes for RubyLLM agent trajectories — record agent runs as DAGs, replay the canonical path, only pay the LLM for net-new paths
Write, validate, and review Agent SKILL.md's directly in Visual Studio Code. SKILL.md Inspector provides live diagnostics for every file named exactly SKILL.md, guided quick fixes, detailed reports, and workspace-wide checks for naming and scope conflicts.
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