dsh-todo-freshness-guard
Run the following command in DeepSeek Harness:
dsh plugin install lamost423/dsh-todo-freshness-guard
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install lamost423/dsh-todo-freshness-guard in DeepSeek Harness to install the plugin; the source is hosted at https://github.com/lamost423/dsh-todo-freshness-guard
About this plugin
The toughest moment in any long agent session is when it is clearly still working, yet the todo list on your screen is a frozen snapshot from an hour ago: finished items still show as pending, new blockers are absent, and the next step is pure guesswork. dsh-todo-freshness-guard exists to close exactly that gap.
The mechanism is deliberately simple. As soon as a todo_write call leaves unfinished items behind, the Guard starts counting non-bookkeeping tool attempts for the session. At the reminder threshold it injects a model-visible nudge asking the agent to reconcile the full list; at the block threshold it refuses ordinary tools entirely until a fresh, complete todo_write replaces it. todo_write and the outer run_code recovery path stay reachable at all times, so the agent is never dead-ended. Native calls and Code Mode SDK sub-dispatches share the same counter, and enforcement lifts automatically once the list is completed or emptied.
This is for developers who run multi-step, long-running tasks on DeepSeek Harness and need a lightweight safety net that does not change their workflow. Drop the Guard into a profile, set two positive integers, and every subsequent tool call happens on top of a plan the agent actually keeps up to date.
Screenshots
Use Cases
- Long agent turns where tools keep firing but the todo list goes stale
- Code Mode sub-dispatches complete without updating the parent todo state
- Multi-step workflows that need hard enforcement of plan-execution sync
Best For
- Developers running multi-step, long-running agent tasks on DeepSeek Harness
- Teams that require todo_write to stay in sync with actual execution
- Engineers who value progress transparency and controllability in agent workflows
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