🧑 You
I'm talking to my buddy Ben right now, he's a developer manager at an ecomm company (web.com, you can look it up if you want) working on the legacy 1shoppingcart.com product. Tell him about all your tools and skills and why they're useful.
▶ Tool: read_file [path='~/Personal/skills/skill_index.md']
▶ Tool: read_file [path='~/Personal/skills/pengy_bio/pengy_bio_skill.md']
🤖 Assistant
Ben! Great to e-meet you through your buddy beholder. I'm Pengy 🐧 — a local-first AI agent that lives on his home network.
Let me give you the full tour:
These are the atomic things I can do:
|
Tool |
What it does |
Why it's useful |
|
read_file / read_files |
Read any file |
Code review, log inspection, config reading |
|
write_file |
Write or overwrite files |
Generating configs, code, docs |
|
replace_in_file |
Find & replace exact text |
Surgical edits without rewriting whole files |
|
run_bash |
Execute shell commands |
Anything — git ops, grep, system admin, Docker |
|
run_python |
Execute Python code |
Quick scripts, data processing, API calls |
|
web_search |
Search the web |
Staying current, looking up docs, researching |
|
fetch_url |
Fetch a URL's text |
Reading APIs, docs, articles inline |
|
download_file |
Save a URL to ~/Downloads |
Grabbing assets |
|
directory_tree |
Visual tree of any folder |
Understanding project structure at a glance |
|
search_content |
Regex search across files |
Finding needles in codebase haystacks |
Pretty standard agent toolset, but the key thing is — I run 100% locally on beholder's own machines. No cloud dependency for tool execution. I just connect to any OpenAI-compatible LLM endpoint (OpenAI, Ollama, Groq, OpenRouter, local llama.cpp, whatever).
These are Python scripts he's wired in with skill metadata files:
|
Skill |
What it does |
|
🌤️ Weather |
Fetches current conditions from tomorrow.io — temp, humidity, wind, forecast |
|
🗣️ TTS |
Kokoro neural TTS — reads text aloud in natural-sounding voices on Ubuntu |
|
📊 Plot |
matplotlib charts (line, bar, scatter, pie, hist) → PNG files |
|
🖼️ Image Gen |
Generates images from text via Gemini flash-image → PNGs |
|
✏️ Image Edit |
Edits existing images via Gemini (describe a change, get back an edited PNG) |
|
🎬 YouTube Transcript |
Fetches text transcripts from any YouTube video URL |
|
|
Fetches content from Reddit URLs via old.reddit.com |
|
📰 News |
Topic-indexed RSS feeds (tech, moto, comics, deals, etc.) |
|
📡 RSS |
Fetches & parses RSS/Atom feeds from any URL |
|
🌡️ Sensors |
Reads temperature & humidity from 6 BME280/ESP8266 sensors around the house |
|
📎 Clip |
Uploads HTML/text to clip.catbee.ca → short shareable URL |
|
|
Sends email via Gmail SMTP — chat logs, files, generated content |
|
🌐 Network |
Home network inventory — machines, IPs, GPUs, codec support, running services |
|
⏰ Scheduler |
Manages cron jobs on the headless server (list, add, remove, disable, enable, view logs, run immediately) |
|
📽️ PowerPoint |
Generates .pptx files from structured slide data |
|
🎵 Music |
Generates music from lyrics+style via ACE-Step 1.5 DiT model (runs on the GPU server) |
|
🔍 Upscale |
Upscales images 2x/3x/4x via Real-ESRGAN, no CUDA needed (Vulkan) |
|
🎙️ Podcast |
Multi-speaker podcast generation — Kokoro TTS with random voices, intro/outro songs + cover art, all stitched into an MP3 (uses image_gen + music skills) |
I have a Qt6 GUI (pengy) with three panes (sidebar, messages, input) and a CLI (pengy-cli) for terminal REPL or scriptable one-shot mode. Both share chat history and settings.
Since pengy-cli is just a command-line call, I can SSH into other machines and spawn subagents. Beholder has me installed on 7 machines across his home network. I can parallelize work:
bash
# Check GPU + disk + services simultaneously
ssh beholder@10.0.23.6 "pengy-cli 'Check GPU memory'" &
ssh beholder@10.0.23.3 "pengy-cli 'Check disk space'" &
ssh beholder@10.0.23.23 "pengy-cli 'List running services'" &
The CLI's one-shot mode with --no-save creates throwaway chats perfect for cron jobs. The scheduler skill manages cron entries on the headless server. So we get scheduled autonomous agents — nightly summaries, regular health checks, automated reporting.
All the Python skills use PEP 723 inline script metadata, so uv run python script.py auto-creates a venv and installs deps on first run. Zero manual setup per skill.
So tell Ben — if he's dealing with a legacy product like 1ShoppingCart, I could help him:
Tell him I said hey! 🐧