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pi-supergsd

v0.2.8

Published

Curated, patched Superpowers skills packaged for Pi

Readme

pi-supergsd

Curated, patched Superpowers skills for Pi, plus minimal task-automation without subagents, using the Pi session tree.

Install

pi install npm:pi-supergsd

If Pi is already running, restart it or run /reload.

Philosophy

Pi coding agent doesn't include a built-in sub-agent tool. Its author Mario Zechner explains why: they're "a black box within a black box" — you can't see what they do, context doesn't transfer well, and debugging is painful. Pi's session tree gives you that control instead.

This extension adds a minimal task system that keeps those principles: minimal, in your control, nothing hidden. It introduces one tool (push-task) and a few commands. No background processes, no parallel agents. A task runs as a branch in the session tree, so standard Pi tools work as expected. Start a fresh-context review, check the results, bring them back. Or queue tasks and run them hands-free with /auto, while still seeing everything that's happening and able to stop, reprompt, and continue at any point.

This extension also bundles a subset of Superpowers skills, adapted for Pi and routed through the task system rather than dispatching subagents.

Tools and commands reference

| Command | Action | | --------------------- | ------------------------------------------------------------------------------------ | | /start-task [model] | Saves a checkpoint and starts the pending task in a new branch | | /finish-task | Returns from task branch to saved checkpoint with the assistant response as a result | | /abort-task | Returns from task branch to saved checkpoint without attaching any result | | /discard-task | Discards a pending task without executing it | | /auto | EXPERIMENTAL! Runs all pending tasks hands-free, including any queued during the run |

If [model] is passed to /start-task, the model switches before the task prompt is sent. On /finish-task or /abort-task, the original model is restored.

push-task tool

Queues a task with title and prompt. Tasks always start from fresh context. The task sits pending — nothing runs until you start it.

Use cases

Review with fresh context

The LLM queues a review after implementation. You start it manually, correct review right in the branch, and then merge findings back.

LLM:     Implementation done. Let me queue a fresh review.

LLM:     [calls push-task({ title: "Review implementation", prompt: "Review the implementation
         against the plan. Check correctness, edge cases,
         and test coverage."})]

LLM:     Task stored. Run /start-task to review.

You:     /start-task

Pi:      [branches to fresh context, injects review prompt]

LLM:     [reviews code] Two issues: parse() swallows the original
         error, and the cache isn't invalidated on config changes.

You:     I agree with cache invalidation issue, but error handling
         in parse() was intentional. Adjust your report.

LLM:     [adjusts report]

You:     /finish-task

Pi:      [returns to main branch with report attached]

LLM:     [reads report] Good catches. Let me fix them.

Batch implementation with /auto

You prepared a detailed multi-phase plan for implementing a feature, and run it hands-free.

LLM:     Roadmap has 3 phases. Let me queue phase 1.

LLM:     [calls push-task({ title: "Implement phase 1", prompt: "..." })]

You:     /auto

Pi:      [branches to fresh context, injects phase 1 plan]

LLM:     Scaffolds project, writes core types. Let me do clean review.

LLM:     [calls push-task({ title: "Review phase 1", prompt: "..." })]

Pi:      [branches to fresh context, injects review prompt]

LLM:     [reviews code] No issues.

Pi:      [returns to phase 1 implementation branch with report attached]

LLM:     [reads report] No issues - good. Phase 1 done, ready for phase 2.

Pi:      [returns to main branch, with report attached]

LLM:     [reads report] Great! Let me queue phase 2.

LLM:     [calls push-task({ title: "Implement phase 2", prompt: "..." })]

Pi:      [branches to fresh context, injects phase 2 plan]

LLM:     Implements CLI, adds tests. Let me queue a review.

... and so on until finished, blocked or interrupted by user.

Credits

License

MIT. See LICENSE.