wayfinder-dashboard
Run the following command in DeepSeek Harness:
dsh plugin install Gyanano/wayfinder-dashboard
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install Gyanano/wayfinder-dashboard in your terminal to install; the full source is available at https://github.com/Gyanano/wayfinder-dashboard.
About this plugin
Some tasks are too large for a single conversation. You start with a vague direction, but landing the work requires a dozen dependent decisions, each layered on the last. Wayfinder Dashboard brings Matt Pocock's Wayfinder methodology into the DeepSeek Harness web interface, turning that kind of work into an interactive decision graph: nodes are decision tickets, edges are dependencies, and the chart reads top-down from origin to destination.
The core mechanism is a clear human-and-AI split. The Agent derives the next layer, dispatches research, and advances the frontier, but it has no tool to make decisions on your behalf — every human-in-the-loop node must be closed by you with /wf-decide. Research returns evidence, never verdicts. Dependencies gate execution order without blocking you from reading any node at any time. A graph is bound to one workspace, and a single repository can hold multiple graphs that never cross.
Built for developers who use Harness to decompose complex projects, structure vague requirements into decision chains, and keep final decision authority in human hands. Open the web interface to see your workspace graph list, start a new chart, dispatch research, and advance the frontier — all within one session.
Use Cases
- Breaking a vague product direction into an actionable decision chain and advancing it layer by layer
- Within a Harness session, letting the Agent derive and research while closing each HITL node with /wf-decide
- Maintaining multiple workspace-bound graphs per repository, each targeting a separate destination without crossing
Best For
- Developers who decompose large projects inside Harness
- Engineering teams that prefer structured planning before execution
- Architects who want AI-assisted derivation while keeping final decision authority in human hands
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