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ztl34245881-commits/dsh-task-planner ↗★ 2

dsh-task-planner

Task planning with experience muscle-memory for DeepSeek Harness: condition-reflex recall of past solutions + LLM-driven capability matching + auto-persisted lessons. Zero keys, zero hard-coded paths.

AI Analysis

核心用途是在复杂任务开始前进行规划，并自动沉淀、复用历史经验。适合需要提升 Agent 复杂任务规划成功率和经验积累能力的场景。

memory
Package
dsh-task-planner
Version
1.0.0
License
MIT
Last updated
Aug 14, 2026

Install

$npx -p @deepseek-ai/dsh dsh plugin --profile web add github:ztl34245881-commits/dsh-task-planner

README

Read the full README ↗

Usage

  • plan_task { task, goal?, constraints? } — plan before starting complex work.
  • task_memory save { task, plan, outcome } — persist a lesson (auto-called by plan_task for the draft).
  • task_memory recall { task } — condition-reflex lookup.
  • task_memory list — show all lessons.

Lesson lifecycle

  1. plan_task writes a draft lesson (status: draft) automatically.
  2. When the task closes, the agent updates it with the outcome (status: verified).
  3. A lesson reused successfully 3× → promote to a formal skill. A lesson rejected 2× → mark obsolete.