dsh-autocount-cloud
Run the following command in DeepSeek Harness:
dsh plugin install teckyuen/dsh-autocount-cloud
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install teckyuen/dsh-autocount-cloud in your DeepSeek Harness terminal to install the plugin; full source at https://github.com/teckyuen/dsh-autocount-cloud
About this plugin
If you are building agent workflows in DeepSeek Harness and need command-level interaction with AutoCount Cloud, dsh-autocount-cloud fills a tooling gap that used to require hand-rolled API calls and polling loops. Reading a command schema, dispatching a command to the connector queue, checking status by ID, or submitting and waiting for a final result were all things you had to wire together yourself — fragile and repetitive.
The plugin packages those steps into four semantic tools: autocount_command_schema lets you inspect the parameter structure of a single command, autocount_submit_command pushes a command into the connector queue, autocount_get_command retrieves status or results by command ID, and autocount_run_command submits and then polls until the command succeeds, fails, or times out. The four tools work independently or in natural inspect → submit → get sequences.
It is aimed at developers and integration teams who connect AutoCount Cloud into DSH workflows. On the safety front, the plugin only calls AutoCount Cloud API endpoints; it stores no credentials, customer data, or direct SQL access. For write operations, final save permissions are still enforced by the AutoCount connector and the AutoCount SDK, so the plugin never oversteps those boundaries.
Use Cases
- Inspect a command schema before dispatching it in a DSH workflow
- Submit an AutoCount Cloud command and poll until it completes or times out
- Retrieve execution status and results by command ID
Best For
- Developers integrating AutoCount Cloud into DeepSeek Harness
- Enterprise integration teams needing connector-level queue interaction
- Architects embedding ERP operations into agent workflows
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