feat(examples): add Linux PipeWire /voice shim, trajectory store maintenance, and portable skills

examples/linux-voice/README.md

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+# Linux PipeWire `/voice` Shim & Local STT/TTS Fallback
+
+On modern Linux distributions using **PipeWire 1.0+** (Ubuntu 24.04+, Fedora 40+, Debian 12/13, Arch Linux, NVIDIA DGX OS), the Antigravity CLI `/voice` command invokes `pw-record` with the `--raw` flag. Because PipeWire's `pw-record` binary does not accept `--raw` (unlike PulseAudio's `parec`), `/voice` exits immediately or captures silent/low-gain audio on USB microphones.
+
+This directory provides a zero-dependency Python 3 standard-library shim (`pw-record`) and installer (`install.sh`) that resolves Linux `/voice` capture end-to-end:
+
+1. **Flag Normalization**: Transparently strips the unsupported `--raw` flag before invoking `/usr/bin/pw-record` when streaming raw PCM (`-`) to `agy`.
+2. **Automatic Physical Microphone Selection**: Queries `pactl list short sources` to select and unmute active hardware USB/analog microphones while ignoring `.monitor` loopback sinks.
+3. **Real-Time DC-Offset Removal & Automatic Gain Control (AGC)**: Uses Python's built-in `array` module to center 16kHz `s16le` PCM frames and normalize quiet microphone levels in real time (`8ms` startup overhead), preventing false `No speech detected` errors.
+4. **Optional Offline Faster-Whisper Fallback**: Tees the captured PCM stream to `/tmp/agy_voice_last.raw` and optionally forwards it to a local Faster-Whisper UNIX domain socket (`/run/user/$UID/voice_dictate.sock`) if cloud transcription is unavailable.
+
+## Installation
+
+```bash
+bash examples/linux-voice/install.sh
+```
+
+Ensure `~/.local/bin` precedes `/usr/bin` in your `PATH`:
+
+```bash
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+### Optional Local STT/TTS Model Bootstrap (`Faster-Whisper` + `Piper` + `Kokoro`)
+
+To keep the Git repository lightweight and free of binary model weights, `install.sh` includes an optional `--with-models` flag that creates an isolated Python virtual environment (`~/.local/share/antigravity-voice/venv`), installs [`requirements.txt`](requirements.txt) (`faster-whisper`, `piper-tts`, `kokoro-onnx`), and downloads the Piper ONNX voice model on demand:
+
+```bash
+bash examples/linux-voice/install.sh --with-models
+ai-say "Antigravity local voice synthesis is active."
+```

examples/linux-voice/ai-say

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+#!/usr/bin/env bash
+# Portable CLI Text-to-Speech helper for Antigravity CLI (Piper TTS default, or --kokoro)
+set -euo pipefail
+
+VOICE_ENV="${AGY_VOICE_ENV:-$HOME/.local/share/antigravity-voice/venv}"
+MODEL_DIR="${AGY_VOICE_MODELS:-$HOME/.local/share/antigravity-voice/models}"
+
+ENGINE="piper"
+if [ "${1:-}" = "--kokoro" ] || [ "${1:-}" = "-k" ]; then
+  ENGINE="kokoro"
+  shift
+fi
+
+TEXT="$*"
+if [ -z "$TEXT" ]; then
+  exit 0
+fi
+
+if [ "$ENGINE" = "piper" ] && [ -x "$VOICE_ENV/bin/piper" ] && [ -f "$MODEL_DIR/en_GB-alan-medium.onnx" ]; then
+  printf "%s\n" "$TEXT" | "$VOICE_ENV/bin/piper" --model "$MODEL_DIR/en_GB-alan-medium.onnx" --output-raw 2>/dev/null | \
+    pw-play --rate 22050 --channels 1 --format s16 - 2>/dev/null || true
+elif command -v spd-say >/dev/null 2>&1; then
+  spd-say "$TEXT"
+fi

examples/linux-voice/install.sh

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+#!/usr/bin/env bash
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+mkdir -p "$HOME/.local/bin" "$HOME/.gemini/antigravity-cli/bin"
+
+install -m 0755 "$SCRIPT_DIR/pw-record" "$HOME/.local/bin/pw-record"
+install -m 0755 "$SCRIPT_DIR/pw-record" "$HOME/.gemini/antigravity-cli/bin/pw-record"
+install -m 0755 "$SCRIPT_DIR/ai-say" "$HOME/.local/bin/ai-say"
+
+echo "Installed PipeWire /voice shim and ai-say wrapper to ~/.local/bin"
+
+if [ "${1:-}" = "--with-models" ]; then
+  VOICE_DIR="${AGY_VOICE_DIR:-$HOME/.local/share/antigravity-voice}"
+  mkdir -p "$VOICE_DIR/models"
+  echo "Bootstrapping isolated Python venv in $VOICE_DIR/venv..."
+  python3 -m venv "$VOICE_DIR/venv"
+  "$VOICE_DIR/venv/bin/pip" install --upgrade pip
+  "$VOICE_DIR/venv/bin/pip" install -r "$SCRIPT_DIR/requirements.txt"
+
+  PIPER_URL_BASE="https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_GB/alan/medium"
+  if [ ! -f "$VOICE_DIR/models/en_GB-alan-medium.onnx" ]; then
+    echo "Downloading Piper TTS voice model (en_GB-alan-medium.onnx)..."
+    curl -fL "$PIPER_URL_BASE/en_GB-alan-medium.onnx" -o "$VOICE_DIR/models/en_GB-alan-medium.onnx"
+    curl -fL "$PIPER_URL_BASE/en_GB-alan-medium.onnx.json" -o "$VOICE_DIR/models/en_GB-alan-medium.onnx.json"
+  fi
+  echo "Local STT/TTS environment ready in $VOICE_DIR"
+else
+  echo "Tip: Run 'bash examples/linux-voice/install.sh --with-models' to auto-install Faster-Whisper, Piper TTS, and Kokoro into an isolated venv."
+fi

examples/linux-voice/pw-record

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+#!/usr/bin/env python3
+"""
+PipeWire Recording Shim for Antigravity CLI (`/voice`) on Linux.
+Uses pure Python standard library (`array`) for zero-dependency startup:
+1. Strips unsupported `--raw` flag passed by Antigravity CLI (`agy`) on PipeWire systems.
+2. Automatically selects and unmutes the primary non-monitor physical microphone input.
+3. Performs real-time DC-offset removal and Automatic Gain Control (AGC) when streaming
+   raw 16kHz s16le PCM to `agy` stdout, preventing `No speech detected` on quiet USB mics.
+4. Optionally forwards `/tmp/agy_voice_last.raw` to a local Faster-Whisper socket
+   (`/run/user/$UID/voice_dictate.sock`) if cloud `audiotranscribe` fails.
+"""
+
+import array
+import math
+import os
+import signal
+import socket
+import subprocess
+import sys
+import time
+
+REAL_PW_RECORD = os.environ.get("AGY_REAL_PW_RECORD", "/usr/bin/pw-record")
+RAW_CAPTURE_PATH = os.environ.get("AGY_RAW_CAPTURE_PATH", f"/tmp/agy_voice_{os.getuid()}.raw")
+SOCKET_PATH = os.environ.get("AGY_WHISPER_SOCKET", f"/run/user/{os.getuid()}/voice_dictate.sock")
+CLI_LOG_PATH = os.path.expanduser("~/.gemini/antigravity-cli/cli.log")
+
+
+def auto_select_mic() -> None:
+    """Select and unmute the first physical non-monitor input source via pactl."""
+    try:
+        out = subprocess.check_output(
+            ["pactl", "list", "short", "sources"],
+            text=True,
+            stderr=subprocess.DEVNULL,
+        )
+        sources = [
+            line.split("\t")[1]
+            for line in out.strip().splitlines()
+            if len(line.split("\t")) >= 2 and ".monitor" not in line.split("\t")[1]
+        ]
+        if not sources:
+            return
+        best = sources[0]
+        for preferred in ["usb-", "input", "mic", "yeti", "audio"]:
+            matches = [s for s in sources if preferred in s.lower()]
+            if matches:
+                best = matches[0]
+                break
+        subprocess.run(["pactl", "set-default-source", best], check=False, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+        subprocess.run(["pactl", "set-source-mute", best, "0"], check=False, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+    except Exception:
+        pass
+
+
+def trigger_local_whisper_fallback() -> None:
+    """Optionally notify a local Faster-Whisper UNIX socket if cloud transcription fails."""
+    try:
+        if not os.path.exists(RAW_CAPTURE_PATH) or os.path.getsize(RAW_CAPTURE_PATH) < 11200:
+            return
+        if not os.path.exists(SOCKET_PATH):
+            return
+        if os.fork() != 0:
+            return
+
+        os.setsid()
+        time.sleep(0.45)
+
+        cloud_failed = os.environ.get("AGY_FORCE_LOCAL_WHISPER", "0") == "1"
+        try:
+            if os.path.exists(CLI_LOG_PATH):
+                with open(CLI_LOG_PATH, "rb") as lf:
+                    lf.seek(max(0, os.path.getsize(CLI_LOG_PATH) - 4096))
+                    tail = lf.read().decode("utf-8", errors="ignore")
+                    if "audiotranscribe:" in tail or "finalizing the transcript failed" in tail:
+                        cloud_failed = True
+        except Exception:
+            pass
+
+        s = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
+        s.settimeout(5.0)
+        s.connect(SOCKET_PATH)
+        cmd = f"TRANSCRIBE_AND_TYPE:{RAW_CAPTURE_PATH}\n" if cloud_failed else f"TRANSCRIBE_RAW:{RAW_CAPTURE_PATH}\n"
+        s.sendall(cmd.encode("utf-8"))
+        s.close()
+    except Exception:
+        pass
+    finally:
+        if "s" in locals():
+            os._exit(0)
+
+
+def main() -> None:
+    raw_mode = "--raw" in sys.argv
+    filtered_args = [a for a in sys.argv[1:] if a != "--raw"]
+
+    auto_select_mic()
+
+    if not raw_mode or "-" not in filtered_args:
+        os.execv(REAL_PW_RECORD, [REAL_PW_RECORD] + filtered_args)
+
+    proc = subprocess.Popen(
+        [REAL_PW_RECORD] + filtered_args,
+        stdout=subprocess.PIPE,
+        stderr=sys.stderr,
+    )
+
+    raw_file = None
+    try:
+        raw_file = open(RAW_CAPTURE_PATH, "wb")
+    except Exception:
+        pass
+
+    def handle_sig(signum, frame):
+        try:
+            proc.terminate()
+        except Exception:
+            pass
+
+    signal.signal(signal.SIGTERM, handle_sig)
+    signal.signal(signal.SIGINT, handle_sig)
+
+    running_gain = 4.0
+    chunk_size = 1280  # 640 samples = 40ms at 16kHz s16le
+
+    try:
+        while True:
+            data = proc.stdout.read(chunk_size) if proc.stdout else b""
+            if not data:
+                break
+
+            if len(data) % 2 == 0 and len(data) > 0:
+                samples = array.array("h")
+                samples.frombytes(data)
+                n = len(samples)
+                mean_val = int(sum(samples) / n)
+                peak = 0
+                sum_sq = 0.0
+                centered = [0] * n
+                for i, v in enumerate(samples):
+                    c = v - mean_val
+                    centered[i] = c
+                    ac = abs(c)
+                    if ac > peak:
+                        peak = ac
+                    sum_sq += c * c
+                rms = math.sqrt(sum_sq / n)
+
+                if rms > 15.0:
+                    target_gain = min(22000.0 / max(peak, 1), 18.0)
+                    running_gain = 0.8 * running_gain + 0.2 * target_gain
+                    g = max(running_gain, 1.5)
+                    out_arr = array.array(
+                        "h",
+                        (max(-32767, min(32767, int(c * g))) for c in centered),
+                    )
+                else:
+                    out_arr = array.array(
+                        "h",
+                        (max(-32767, min(32767, c)) for c in centered),
+                    )
+                out_bytes = out_arr.tobytes()
+            else:
+                out_bytes = data
+
+            if raw_file is not None:
+                try:
+                    raw_file.write(out_bytes)
+                    raw_file.flush()
+                except Exception:
+                    pass
+
+            try:
+                sys.stdout.buffer.write(out_bytes)
+                sys.stdout.buffer.flush()
+            except BrokenPipeError:
+                break
+    finally:
+        if raw_file is not None:
+            try:
+                raw_file.close()
+            except Exception:
+                pass
+        try:
+            proc.terminate()
+            proc.wait(timeout=0.3)
+        except Exception:
+            try:
+                proc.kill()
+            except Exception:
+                pass
+        trigger_local_whisper_fallback()
+
+
+if __name__ == "__main__":
+    main()

examples/linux-voice/requirements.txt

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+faster-whisper>=1.1.0
+piper-tts>=1.2.0
+kokoro-onnx>=0.4.0
+soundfile>=0.12.1
+numpy>=1.26.0

examples/skills/README.md

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+# Community Skills Examples for Antigravity CLI
+
+This directory contains portable, self-contained agent skills that can be installed into `~/.agents/skills/<skill-name>/`:
+
+1. **[`local-llm-web-search`](local-llm-web-search/SKILL.md)**: Zero-API-key live web search, parallel page extraction, and local LLM synthesis via Ollama (`127.0.0.1:11434`) or any OpenAI-compatible local server.
+2. **[`linux-usb-xhci-diagnostics`](linux-usb-xhci-diagnostics/SKILL.md)**: Kernel-register-first Linux USB-C, xHCI link lane (`portli`), USB 2.0 Single-TT vs. Multi-TT hub collision, and DisplayPort diagnostic workflow.
+3. **[`headless-vector-pdf`](headless-vector-pdf/SKILL.md)**: Publication-grade Markdown-to-Print-CSS vector PDF and Graphviz SVG-to-PNG compilation using headless Chromium/Chrome without root privileges.

examples/skills/headless-vector-pdf/SKILL.md

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+---
+name: headless-vector-pdf
+description: Compile Markdown documents and Graphviz DOT diagrams into publication-grade vector PDFs and high-resolution PNGs using headless Chrome or Chromium without root packages.
+---
+
+# Headless Vector PDF & Diagram Compiler
+
+Use this skill when generating printable technical reports, manuals, or architectural diagrams in environments without LaTeX or root package installation privileges.
+
+## 1. Markdown / HTML to Vector PDF
+
+Wrap the rendered HTML body in print-media CSS rules and invoke headless Chrome/Chromium:
+
+```css
+@page { size: letter; margin: 18mm 16mm 20mm 16mm; }
+body { font-family: Georgia, serif; line-height: 1.65; color: #111; }
+pre, code { font-family: monospace; white-space: pre-wrap; word-wrap: break-word; }
+```
+
+```bash
+google-chrome --headless=new --disable-gpu --no-sandbox --print-to-pdf=output.pdf document.html
+```
+
+## 2. Graphviz DOT to High-Resolution PNG Fallback
+
+If `dot -Tpng` fails due to missing Cairo/Pango plugins in user-space, output standard SVG first and rasterize via headless Chrome:
+
+```bash
+dot -Tsvg architecture.dot -o architecture.svg
+google-chrome --headless=new --disable-gpu --no-sandbox --screenshot=architecture.png --window-size=1600,1000 architecture.svg
+```

examples/skills/linux-usb-xhci-diagnostics/SKILL.md

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+---
+name: linux-usb-xhci-diagnostics
+description: Diagnose Linux USB-C ports, xHCI link error counts, Single-TT vs Multi-TT USB 2.0 hub collisions, and GPU DisplayPort clock states via sysfs and debugfs registers.
+---
+
+# Linux USB-C, xHCI & Display Register Diagnostics
+
+Use this skill whenever diagnosing intermittent USB device disconnects (`error -71` / `-EPROTO`), USB hub resets (`clear tt 1`), or external display blanking on Linux workstations. Always inspect kernel hardware registers before speculating about power supplies or physical cables.
+
+## 4-Stage Register Inspection Protocol
+
+1. **Over-Current & Port Power Control (`sysfs`)**:
+   Check whether any physical root port has tripped hardware over-current protection or aggressive autosuspend:
+   ```bash
+   grep -H . /sys/bus/usb/devices/*-port*/over_current_count
+   grep -H . /sys/bus/usb/devices/*-port*/power/control
+   grep -H . /sys/bus/usb/devices/*-port*/usb3_lpm_permit 2>/dev/null
+   cat /sys/module/usbcore/parameters/autosuspend
+   ```
+
+2. **xHCI Link Error Count & SuperSpeed Lane Negotiation (`debugfs`)**:
+   Inspect `/sys/kernel/debug/usb/xhci/*/ports/*/portli` to check `LEC` (Link Error Count) and `RLC`/`TLC` (active RX/TX lanes):
+   ```bash
+   sudo grep -H . /sys/kernel/debug/usb/xhci/*/ports/*/portli
+   ```
+
+3. **USB 2.0 Transaction Translator (Single-TT vs. Multi-TT) Audit**:
+   Inspect `/sys/kernel/debug/usb/devices` for `Cls=09(hub)`:
+   - `Prot=01` indicates a **Single-TT** USB 2.0 hub (all ports share a single 12 Mbps USB 1.1 Transaction Translator).
+   - `Prot=02` indicates a **Multi-TT** USB 2.0 hub (dedicated Transaction Translator per port).
+   - Combining a 12 Mbps Full-Speed isochronous audio device (`#Iso>0`) and 1.5 Mbps Low-Speed HID keyboard/mouse on a `Prot=01` Single-TT hub overflows the periodic frame schedule (`clear tt 1 error -71`). Separate them onto different root ports or a `Prot=02` Multi-TT hub.
+
+4. **Portable Dual-USB-C Monitor Back-Feed Safety**:
+   Never advise plugging an external USB-C PD wall brick into the secondary unlabelled USB-C port of a generic portable monitor while connected to a host computer unless reverse-current diode isolation is verified, as shared `VBUS` rails can back-feed voltage into the host Type-C controller.

examples/skills/local-llm-web-search/SKILL.md

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+---
+name: local-llm-web-search
+description: Augment local Ollama or OpenAI-compatible models (127.0.0.1:11434) with live web search and parallel article extraction without external search API keys.
+---
+
+# Local LLM Web Search Skill (`ollama-web`)
+
+Use this skill when the user wants to run a local model via Ollama (`127.0.0.1:11434`) grounded with live, up-to-date web search results and full-text page extraction.
+
+## Workflow
+
+1. **Discover Local Models Dynamically**:
+   Query `http://127.0.0.1:11434/api/tags` to list installed Ollama models rather than hardcoding model tags.
+2. **Execute Grounded Query**:
+   Run `ollama_web_cli.py` with the target query and optional `--model`:
+   ```bash
+   python3 ~/.agents/skills/local-llm-web-search/ollama_web_cli.py "Latest Linux kernel 6.14 ARM64 features"
+   ```
+3. **Interactive Mode**:
+   Launch an interactive grounded REPL session:
+   ```bash
+   python3 ~/.agents/skills/local-llm-web-search/ollama_web_cli.py -i
+   ```