docs: update GETTING-STARTED.md
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@ -190,9 +190,9 @@ This is genuinely useful once the system is running. It makes working with Claud
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**macOS:** [SuperWhisper](https://superwhisper.com) with a local Parakeet model runs via WhisperKit on the Apple Neural Engine. Audio is processed entirely on-device. System-wide hotkey, inserts into any focused app. Free tier works well. This is the most turnkey option on Mac. Built-in Apple Dictation is a reasonable fallback if you want zero setup.
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**macOS:** [SuperWhisper](https://superwhisper.com) with a local Parakeet model runs via WhisperKit on the Apple Neural Engine. Audio is processed entirely on-device. System-wide hotkey, inserts into any focused app. Free tier works well. This is the most turnkey option on Mac. Built-in Apple Dictation is a reasonable fallback if you want zero setup.
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**Windows:** [OmniDictate](https://github.com/Turbo-Adib/OmniDictate) — free, open-source, uses faster-whisper as the backend. Push-to-talk via Right Shift (configurable), types directly into any focused Windows application. NVIDIA GPU with CUDA gives best performance; CPU-only mode works but is slower on larger models. Available as a `.exe` installer from the Releases page. Actively maintained — v2.0 shipped December 2025. Windows SmartScreen will warn on first run (unsigned binary); click through.
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**Windows:** [OmniDictate](https://github.com/gurjar1/OmniDictate) — free, open-source, uses faster-whisper as the backend. Push-to-talk via Right Shift (configurable), types directly into any focused Windows application. NVIDIA GPU with CUDA gives best performance; CPU-only mode works but is slower on larger models. Available as a `.exe` installer from the Releases page. Actively maintained — v2.0 shipped December 2025. Windows SmartScreen will warn on first run (unsigned binary); click through.
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**Linux:** [WhisperTux](https://github.com/medmunds/whispertux) — free, open-source, uses whisper.cpp as the backend. Global keyboard shortcut for start/stop, auto-injects text into the focused application. Works without a GPU — whisper.cpp runs on plain x86 with AVX. GPU acceleration supported if available. Works on GNOME and KDE. Install via `git clone` + `python3 setup.py` which handles dependencies, model download, and service registration. Last commit February 2026.
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**Linux:** [WhisperTux](https://github.com/cjams/whispertux) — free, open-source, uses whisper.cpp as the backend. Global keyboard shortcut for start/stop, auto-injects text into the focused application. Works without a GPU — whisper.cpp runs on plain x86 with AVX. GPU acceleration supported if available. Works on GNOME and KDE. Install via `git clone` + `python3 setup.py` which handles dependencies, model download, and service registration.
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One practical note: voice dictation produces transcription artefacts — misheard words, missing punctuation, run-on sentences. Claude handles this well if you prompt it naturally. You do not need to clean up every word before submitting.
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One practical note: voice dictation produces transcription artefacts — misheard words, missing punctuation, run-on sentences. Claude handles this well if you prompt it naturally. You do not need to clean up every word before submitting.
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@ -235,8 +235,8 @@ Once the baseline is stable, these are natural next layers — each independent,
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| Layer | What it adds | Requires |
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| Layer | What it adds | Requires |
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| Private Git hosting | Self-hosted Forgejo instead of GitHub | A VPS or home server |
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| Private Git hosting | Self-hosted Forgejo instead of GitHub | A VPS or home server |
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| Infrastructure monitoring | Prometheus + Grafana + Alertmanager | A VPS |
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| Infrastructure monitoring | Prometheus + Grafana + Alertmanager | Any always-on machine — local to learn, VPS for reliability |
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| Log aggregation | Loki + Grafana Alloy | A VPS |
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| Log aggregation | Loki + Grafana Alloy | Any always-on machine |
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| Secure remote access | WireGuard VPN | A VPS |
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| Secure remote access | WireGuard VPN | A VPS |
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| Local AI inference | Ollama + Open WebUI | GPU with adequate VRAM |
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| Local AI inference | Ollama + Open WebUI | GPU with adequate VRAM |
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| Multi-agent workers | Codex + Gemini alongside Claude | Existing workspace |
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| Multi-agent workers | Codex + Gemini alongside Claude | Existing workspace |
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@ -312,19 +312,55 @@ how they hand off work, and what prevents them from conflicting.
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---
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---
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## Files to Create in Your Own Repo
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## Bootstrap Your Repo with Claude
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These are the documents that make an AI-assisted repo work well. None of them are magic — they are just Markdown files with clear purposes. Build them gradually as you need them.
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Once the baseline is running, use these prompts to build the foundation documents. Each one is a single conversation — paste the prompt, answer Claude's questions, and commit the result.
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| File | Purpose | Create it when… |
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**Create your session entrypoint document:**
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```
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| `README.md` | Human-facing landing page — what this is, current state, key links | Day one |
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I am setting up a Git repo as a control plane for AI-assisted development.
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| `ENTRYPOINT.md` | Agent session startup — what to read first, environment facts, execution boundaries | Once you have more than one doc |
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| `AGENTS.md` | Operating contract for AI agents — what they can do, what requires approval | Before doing serious work with agents |
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| `docs/system-plan.md` | Planning source of truth — what is built, what is open, what is next | When you have infrastructure to track |
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| `docs/open-loops.md` | Persistent backlog across sessions — so nothing falls through the cracks | When unresolved items start accumulating |
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| `bootstrap.sh` | Idempotent setup script — verifies the workspace is in the expected state after rebuilds | Once your setup has more than 3 steps |
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| `.claude/rules/` | Repo-level rules loaded every Claude session — safety, style, workflow | When you have patterns you keep repeating |
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| `docs/vendor-docs/` | Current third-party documentation fetched and stored locally | Before writing any code that uses an external library |
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**The most important habit:** Ask Claude to fetch current docs before writing any code that uses a third-party library, API, or tool. Training data is frozen. The docs are not.
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Create an ENTRYPOINT.md for this repo that:
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- Lists the key documents an AI agent should read before starting work
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- States what this repo is and what it is for
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- States the execution boundaries (what runs in the container vs what runs on the host)
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- States where secrets are kept and that they must never enter the repo
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Ask me questions about my setup before writing anything.
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```
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**Create your agent operating contract:**
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```
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Create an AGENTS.md for this repo that defines:
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- What AI agents are permitted to do autonomously
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- What requires explicit human approval before proceeding
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- The Git branch model (who works on which branch)
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- What agents must never do (commit secrets, push to main directly, etc.)
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Ask me about my setup and which agents I am using before writing anything.
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```
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**Create your open loops document:**
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```
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Create a docs/open-loops.md for this repo.
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This file tracks unresolved items across sessions — things that are in progress,
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decisions that have not been made, or work that is blocked. It should be read at
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the start of every session so nothing falls through the cracks between conversations.
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Start it with the current open items from our conversation so far.
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```
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**Scaffold the full foundation in one pass:**
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```
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I have a new Git repo for AI-assisted development. I need you to create the
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following foundation documents, asking me questions before writing each one:
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1. README.md — what this repo is, current state, key links
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2. ENTRYPOINT.md — agent session startup, read order, execution boundaries
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3. AGENTS.md — what agents can and cannot do, branch model
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4. docs/open-loops.md — persistent backlog of unresolved items
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For each document: ask me the questions you need answered, write a first draft,
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show it to me, and wait for approval before moving to the next one.
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```
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