License-aware Markdown snapshots collected from GitHub
Translations: Translations in progress: This is my multi-month study plan for becoming a software engineer for a large company. Required: Note this is a study plan for software engineering, not frontend engineering or full-stack development.
The full voice I/O stack, running locally on your machine. voicebox.sh • Docs • Download • Features • API • Troubleshooting Click the image above to watch the demo video on voicebox.sh Voicebox is a local-first AI voice studio — a free and open-source alternative to ElevenLabs and WisprFlow in one app.
Date: 2026-02-19 Status: Approved Scope: lib/brainstorm-server/, skills/brainstorming/visual-companion.md, tests/brainstorm-server/ During visual brainstorming, Claude runs wait-for-feedback.sh as a background task and blocks on TaskOutput(block=true, timeout=600s). This seizes the TUI entirely — the user cannot type to Claude while visual brainstorming is running.
Goal: Finish PR #1720's final hardening fixup with test-first changes, clean rebase state, and reviewer-ready evidence. Spec: docs/superpowers/specs/2026-06-11-visual-companion-final-hardening-fixup-design.md Architecture: Keep the companion zero-dependency and local-first.
Browser-based visual brainstorming companion for showing mockups, diagrams, and options. The test: would the user understand this better by seeing it than reading it?
Make superpowers skills work in the Codex App's sandboxed worktree environment without breaking existing Claude Code or Codex CLI behavior. Ticket: PRI-823 The Codex App runs agents inside git worktrees it manages — detached HEAD, located under $CODEXHOME/worktrees/, with a Seatbelt sandbox that blocks git checkout -b, git push, and network access.
:wave: This repo is maintained by @eps1lon and @filiptammergard. We're so happy you want to try out React with TypeScript!
Date: 2026-06-11 Status: Draft for Drew review Finish the PR #1720 visual companion hardening pass so the branch is ready for Jesse review with clean security behavior, deterministic tests, and a PR diff that contains only the companion work. This is a fixup on top of the existing auth hardening design.
Work with code and text, run processes, and automate tasks, going far beyond other AI editors - while using host client subscriptions instead of API token costs. The Desktop Commander App gives you everything the MCP server does, plus: 👉 Download the App (macOS & Windows) All of your AI development tools in one place.
why use many token when few do trick Make your AI coding agent talk like a caveman. 65% fewer output tokens on prose, 8.5% on agentic coding runs .
Integrate the DeepSeek API into popular softwares. Access DeepSeek Open Platform to get an API key.
Status: Proposed experiment ladder (not implementation). Each rung ships only with its gate evidence; abort any rung whose gates fail.
with maintainer sign-off after the RED baseline did not reproduce blind stale-ledger adoption. 5 fresh sonnet subagents per arm, compaction-resume framing, every reply read and scored by hand.
Superpowers is a complete software development methodology for your coding agents, built on top of a set of composable skills and some initial instructions that make sure your agent uses them. Give your agent Superpowers: Claude Code, Antigravity, Codex App, Codex CLI, Cursor, Factory Droid, Gemini CLI, GitHub Copilot CLI, Kimi Code, OpenCode, Pi.
Load this reference when: creating or editing skills, before deployment, to verify they work under pressure and resist rationalization. Testing skills is just TDD applied to process documentation.
This guide was created by Brex for internal purposes. It's based on lessons learned from researching and creating Large Language Model (LLM) prompts for production use cases.
Goal: Add full superpowers support for OpenCode.ai with a native JavaScript plugin that shares core functionality with the existing Codex implementation. Architecture: Extract common skill discovery/parsing logic into lib/skills-core.js, refactor Codex to use it, then build OpenCode plugin using their native plugin API with custom tools and session hooks.
Goal: Make superpowers defer to native harness worktree systems when available, fall back to manual git worktrees when not, and fix three known finishing bugs. Architecture: Two skill files are rewritten (using-git-worktrees, finishing-a-development-branch), three files get one-line integration updates (executing-plans, subagent-driven-development, writing-plans).
Make subagent-driven-development's per-task reviews cheaper and faster without weakening them, by scoping per-task review prompts to the task and stopping redundant work — while final branch review stays broad. Per-task code quality reviewers in SDD routinely do branch-review-scale work on single-task diffs.
~54% less code (up to 94%) · ~20% cheaper · ~27% faster · 100% safe Measured on real Claude Code sessions editing a real open-source repo (FastAPI + React), against the same agent with no skill. ~54% is the mean across 12 feature tasks (Haiku 4.5, n=4); it reaches 94% where an agent over-builds (a date picker) and is near zero where the code is already minimal.
License-aware Markdown snapshots collected from GitHub
Translations: Translations in progress: This is my multi-month study plan for becoming a software engineer for a large company. Required: Note this is a study plan for software engineering, not frontend engineering or full-stack development.
The full voice I/O stack, running locally on your machine. voicebox.sh • Docs • Download • Features • API • Troubleshooting Click the image above to watch the demo video on voicebox.sh Voicebox is a local-first AI voice studio — a free and open-source alternative to ElevenLabs and WisprFlow in one app.
Date: 2026-02-19 Status: Approved Scope: lib/brainstorm-server/, skills/brainstorming/visual-companion.md, tests/brainstorm-server/ During visual brainstorming, Claude runs wait-for-feedback.sh as a background task and blocks on TaskOutput(block=true, timeout=600s). This seizes the TUI entirely — the user cannot type to Claude while visual brainstorming is running.
Goal: Finish PR #1720's final hardening fixup with test-first changes, clean rebase state, and reviewer-ready evidence. Spec: docs/superpowers/specs/2026-06-11-visual-companion-final-hardening-fixup-design.md Architecture: Keep the companion zero-dependency and local-first.
Browser-based visual brainstorming companion for showing mockups, diagrams, and options. The test: would the user understand this better by seeing it than reading it?
Make superpowers skills work in the Codex App's sandboxed worktree environment without breaking existing Claude Code or Codex CLI behavior. Ticket: PRI-823 The Codex App runs agents inside git worktrees it manages — detached HEAD, located under $CODEXHOME/worktrees/, with a Seatbelt sandbox that blocks git checkout -b, git push, and network access.
:wave: This repo is maintained by @eps1lon and @filiptammergard. We're so happy you want to try out React with TypeScript!
Date: 2026-06-11 Status: Draft for Drew review Finish the PR #1720 visual companion hardening pass so the branch is ready for Jesse review with clean security behavior, deterministic tests, and a PR diff that contains only the companion work. This is a fixup on top of the existing auth hardening design.
Work with code and text, run processes, and automate tasks, going far beyond other AI editors - while using host client subscriptions instead of API token costs. The Desktop Commander App gives you everything the MCP server does, plus: 👉 Download the App (macOS & Windows) All of your AI development tools in one place.
why use many token when few do trick Make your AI coding agent talk like a caveman. 65% fewer output tokens on prose, 8.5% on agentic coding runs .
Integrate the DeepSeek API into popular softwares. Access DeepSeek Open Platform to get an API key.
Status: Proposed experiment ladder (not implementation). Each rung ships only with its gate evidence; abort any rung whose gates fail.
with maintainer sign-off after the RED baseline did not reproduce blind stale-ledger adoption. 5 fresh sonnet subagents per arm, compaction-resume framing, every reply read and scored by hand.
Superpowers is a complete software development methodology for your coding agents, built on top of a set of composable skills and some initial instructions that make sure your agent uses them. Give your agent Superpowers: Claude Code, Antigravity, Codex App, Codex CLI, Cursor, Factory Droid, Gemini CLI, GitHub Copilot CLI, Kimi Code, OpenCode, Pi.
Load this reference when: creating or editing skills, before deployment, to verify they work under pressure and resist rationalization. Testing skills is just TDD applied to process documentation.
This guide was created by Brex for internal purposes. It's based on lessons learned from researching and creating Large Language Model (LLM) prompts for production use cases.
Goal: Add full superpowers support for OpenCode.ai with a native JavaScript plugin that shares core functionality with the existing Codex implementation. Architecture: Extract common skill discovery/parsing logic into lib/skills-core.js, refactor Codex to use it, then build OpenCode plugin using their native plugin API with custom tools and session hooks.
Goal: Make superpowers defer to native harness worktree systems when available, fall back to manual git worktrees when not, and fix three known finishing bugs. Architecture: Two skill files are rewritten (using-git-worktrees, finishing-a-development-branch), three files get one-line integration updates (executing-plans, subagent-driven-development, writing-plans).
Make subagent-driven-development's per-task reviews cheaper and faster without weakening them, by scoping per-task review prompts to the task and stopping redundant work — while final branch review stays broad. Per-task code quality reviewers in SDD routinely do branch-review-scale work on single-task diffs.
~54% less code (up to 94%) · ~20% cheaper · ~27% faster · 100% safe Measured on real Claude Code sessions editing a real open-source repo (FastAPI + React), against the same agent with no skill. ~54% is the mean across 12 feature tasks (Haiku 4.5, n=4); it reaches 94% where an agent over-builds (a date picker) and is near zero where the code is already minimal.