Plugin directory / Productivity / dsh-task-checklist
dsh-task-checklist
Verified · install-tested on dsh fff122
What it does
Local task checklist plugin for DeepSeek Harness.
Works — verified, early-stage project
Local task checklist plugin for DeepSeek Harness. It installs cleanly and boots without issues in our testing. It's early-stage but functional.
“Verified” means our automated CI actually ran dsh plugin add in a clean profile and it booted — nothing more. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.
README
dsh-task-checklist
A local task checklist plugin for DeepSeek Harness. It lets an Agent create tasks, filter them by state or tag, mark work complete, and export a clean Markdown checklist.
All task data stays in the current working directory under .dsh/task-checklist/tasks.json. The plugin does not send task data over the network.
Quick install
Requirements
You need Node.js 22 or newer, pnpm, and a DeepSeek Harness installation that supports JavaScript or TypeScript plugins.
Step 1: Download and build
Copy and run:
git clone https://github.com/fff122/dsh-task-checklist.git
cd dsh-task-checklist
pnpm install
pnpm build
Step 2: Create the plugin configuration
Run this command from the repository root:
cat > task-checklist.patch.yml <<EOF
- insert:
- id: dsh-task-checklist
name: '$PWD/dist/src/index.js'
EOF
The plugin path is absolute because the Harness patch loader requires an absolute path.
Step 3: Start Harness with the plugin
If Harness is installed as a command:
dsh web --patch "$PWD/task-checklist.patch.yml"
Otherwise, run:
npx @deepseek-ai/dsh web --patch "$PWD/task-checklist.patch.yml"
Verify the installation
Ask the Agent:
创建一个任务:准备周五的项目演示。标签用 work 和 demo,优先级为 high。
If the plugin is loaded, the Agent can use task_create. You can then ask it to list unfinished tasks, complete a task by id, or export a Markdown checklist.
Available tools
| Tool | Purpose |
|---|---|
task_create |
Create a task with a title and optional details, tags, and priority. |
task_list |
List tasks, optionally filtered by todo or done status and matching tags. |
task_complete |
Mark a task complete using its id. |
task_export_markdown |
Export matching tasks as a Markdown checklist. |
Data and behavior
Each Harness working directory has its own checklist at .dsh/task-checklist/tasks.json. Writes are atomic, so an interrupted write cannot leave a partially written data file. Task identifiers are returned by task_create and task_list; use them with task_complete.
The tag filter is an all tags filter. For example, filtering by work and demo returns only tasks that have both tags.
Updating the plugin
From the cloned repository:
git pull
pnpm install
pnpm build
Restart Harness with the same patch command after rebuilding.
Development
Run the complete package quality gate from the repository root:
pnpm run format:check
pnpm run typecheck
pnpm run test
pnpm run build
The implementation is deliberately separated into small modules:
src/
index.ts # Harness entry point and tool registration
task-schema.ts # Task types and input normalization
task-store.ts # Local persistence, filtering, completion, and export
test/
index.test.ts
mount.test.ts
task-schema.test.ts
task-store.test.ts
For the plugin model and patch overlay format, see the official DeepSeek Harness plugin guide.
Install
Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:
dsh plugin add dshbase-catalog Then say "install dsh-task-checklist for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.
This plugin is GitHub source (not published to npm) — install it straight from the repo:
Web profile:
dsh plugin --profile web add github:fff122/dsh-task-checklist Headless (CLI) profile:
dsh plugin --profile headless add github:fff122/dsh-task-checklist Test report
Verified: L1 install + L2 load + L3 runtime from GitHub source on dsh 0.1.0-rc.6.
When to use it
Connect dsh to the tools you actually work in — office docs, task boards, or chat apps — so it fits your workflow.
Who it's for
Users who want the agent to operate inside their existing productivity stack instead of a silo.
For developers — extending it
Integrations and adapters are the seams — add a new app connector, richer read/write, or workflow triggers.