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Show HN: Collie – a local AI harness that runs the browser, desktop and code

Collie, a new local AI harness that runs on a user's machine, can drive the real browser, desktop, screen, and code while keeping everything private and verified. The tool, built by Collie HQ, features a coding agent with self-verifying repair loops, a Chrome extension for browser control, an ambient desktop wallpaper, screen recording, and a phone remote via an iOS companion app. Collie is terminal-first and supports editors through an open protocol, with a one-click Windows installer available on GitHub.

read9 min views1 publishedJul 30, 2026
Show HN: Collie – a local AI harness that runs the browser, desktop and code
Image: source

A coding agent that lives on your computer — and can actually run it.

Local and private. It reaches your real environment — your logged-in browser, your desktop, your screen, your files — and proves its work by running it.

collie.run · collie -p "fix the bug"

· collie web

Most coding agents live in a cloud tab or an editor pane and can only touch the files you hand them. Collie runs on your machine — so it works the way you already do: it drives your real logged-in browser, arranges your desktop, records your screen, takes tasks from your phone, and edits your code. Nothing leaves your computer unless you send it there; there's no account and no telemetry.

And it doesn't just claim to be done. When Collie fixes something it writes a reproduction that must fail on the broken code, makes the smallest edit that flips it, and re-runs the assertion — a run isn't "done," it's verified ✓.

It's local, and it reaches your real world. A cloud agent can read a repo. Collie can open the site in the browser you're already logged into, click through the actual flow, watch what happens on your screen, and change the code — all on one machine, all under your control. That's a different class of task: not "edit these files," but "get this working, end to end."

The range is the proof. Collie isn't a coding agent with a pile of unrelated features bolted on. The breadth below — the desktop console, the browser control, the screen recorder, the phone remote — is there because Collie's coding agent built all of it. The features are the benchmark: a harness strong enough to ship its own desktop app and iOS companion is strong enough for your bug.

Capability What it means
🧠 Coding agent
Semantic code navigation, syntax-gated edits, and a self-verifying repair loop — the core, covered below.
🌐 Your real browser
A Chrome extension lets Collie act in your logged-in browser — the real session, real cookies — so it can operate sites, not just scrape them. Every action is a fenced, CSRF-checked localhost call.
🖥️ Living desktop
collie web powers an interactive ambient wallpaper: clock, weather, an app dock, projects, a music player (real audio + synced karaoke lyrics), and a command bar — all agent-manageable via one JSON config. When Collie is working, the wallpaper becomes a live star-map of your code.
🎬 Screen recorder
collie record captures screen + camera + mic (Windows and macOS) — a built-in way to demo or document a run.
📱 Phone remote
Pair once by scanning a code; then tail runs and start new ones from your phone — on the same Wi-Fi (--lan ) or anywhere through a relay (--remote ), with the companion iOS app.
🔌 Everywhere else
Terminal, browser GUI, VS Code, and any ACP editor (Zed/JetBrains/neovim) — one harness, every surface.

Collie is terminal-first and reaches editors through an open protocol, not a bespoke extension:

Surface Command Reaches
Terminal
collie (TUI) · collie -p "task"
anywhere — SSH, CI, tmux
Browser GUI
collie web
chat, the live verification gate, diffs, the star-map, the ambient desktop, settings
iPhone
collie web --lan (same Wi-Fi) or --remote (anywhere, via the relay) + the companion app
scan the pair code once, then run from the phone
VS Code
the bundled vscode-collie extension
Collie docked in a sidebar panel (manages its own server)
Editors (ACP)
collie acp
Zed · JetBrains · neovim · VS Code — one adapter, every

Streaming / CIcollie run "task" --stream-json

Windows — one click. Download ** Collie-Setup.exe** from the

latest releaseand double-click it. A small app-style installer lays down a self-contained runtime (Python + Collie + semantic memory, nothing to preinstall) and opens Collie in a native desktop window. On first launch you

pick a brain— an existing Claude, Codex, or Grok login is detected and connects in one click; or paste an API key.

macOS / Linux — pip. The core is stdlib-only, so the base install is tiny:

pip install -e ".[local,dev]"      # from a clone (PyPI publish is planned)
collie setup                       # optional deps, pre-download the memory model, pick a provider
collie                             # the terminal chat (TUI) opens

No account, no telemetry, and the core has zero third-party dependenciesmock

and ollama

run without any key, and memory works out of the box on BM25 keyword recall.

Optional extras: pip install ".[local,tui,search]"

local

(semantic memory: granite-107m via onnxruntime, ~55MB, multilingual), tui

(rich terminal chat), search

(keyless web search), acp

(editor protocol), browser

(Playwright — only for collie browser-bridge --browser

, a managed Chromium with the extension preloaded, for CI or when you'd rather not use your own Chrome). Per-OS setup — especially the real-browser bridge (collie browser-bridge

  • harness/browser_ext/

) — is in ** docs/PLATFORMS.md**.

collie                     # terminal chat (TUI); first run picks a provider
collie web                 # browser GUI — chat, live gate, diffs, star-map, ambient desktop
collie selftest            # $0 deterministic end-to-end (mock model, real tools + memory)

DEEPSEEK_API_KEY=... collie -p "fix the off-by-one in utils/timeparse.py"

collie run "fix the bug" --json          # final result object (tokens, cost, verified)
collie run "fix the bug" --stream-json   # live NDJSON: tool · edit · repro-gate · receipt

collie run "summarize app.py" --provider ollama --model qwen2.5-coder:7b

collie loop --goal "get the suite passing" --until "pytest -q" --max 8

collie pack "fix the failing test" -n 3 --check "pytest -q" --apply

collie acp                 # serve as an ACP agent (an editor spawns this over stdio)

Providers: mock

, ollama

, anthropic

, anthropic-oauth

, and OpenAI-compatible presets deepseek

· qwen

/dashscope

· openrouter

· moonshot

· groq

· zhipu

· openai

.

Everything above rests on a small, honest harness. This is what's under it.

  locate   code_search "parse_duration compound units"   · 4 hits
           › utils/timeparse.py:42  _parse  ············· 0.91

  repro    wrote repro.py · assert parse_duration("1h30m") == 5400
           ✗ FAILING  › got 1800, want 5400              ← gate armed

  edit     utils/timeparse.py  ································· +1 −1
           43 │- total = SECONDS[unit] * int(val)
           43 │+ total += SECONDS[unit] * int(val)

  verify   python repro.py
           ✓ PASSING  › parse_duration("1h30m") == 5400   ← gate green

  ✓ verified in 12.8s · Δ +1 −1 · 3,410 tok · $0.006

Other agents check "did the test not error." Collie's gate is stronger: the reproduction carries an assert actual == expected

derived from the issue, so a plausible-but-wrong edit fails loudly and drives another repair round. This ** assert-verify** loop is the core of the harness — a wrong edit never silently ships as "done." The same idea scales up:

collie loop

stops when a real shell check exits 0, and collie pack

picks the best of N attempts by what actually passes.

                      ┌──────────────── loop.Harness ────────────────┐
   task ─────────────▶│  compose → complete → run tools → verify ✓   │
                      └──┬──────────────┬──────────────┬─────────────┘
     ┌───────────────────┘              │              └───────────────────┐
     ▼                                  ▼                                  ▼
 ContextComposer                  ModelProvider                     ToolRegistry
 STABLE/CONTEXT/VOLATILE          OpenAI-compat · Anthropic ·       read/write/edit/bash/
 + token budgeter                 Ollama · subscription-OAuth       grep/glob + code_search
     ▼                                  │                                  │
 memory.SqliteMemory                    ▼                            recorder.Recorder
 hybrid recall (BM25+dense+RRF)   emit → stream-json / ACP          runs.db (+ dashboard)
Seam (abstract base) shipped impl
ModelProvider
OpenAICompat (DeepSeek/Qwen/GLM/OpenRouter…) · Anthropic · Ollama · subscription-OAuth
ToolRegistry
read/write/edit (syntax-gated) · bash · grep · glob · · code_search + web_search (keyless) · web_fetch · plan · browser · undo MCP (deferred tier + load_tools )
EmbeddingProvider
OnnxEmbedding granite-107m (Apache, 55MB, multilingual) · bge-m3 / e5 · jina-v3 opt-in · BM25-only when no model
SqliteMemory
CORE + facts + FTS5 + cosine, hybrid RRF + optional rerank + consolidation
ContextComposer
STABLE/CONTEXT/VOLATILE + auto-prefetch · a ~1K-token fixed prefix (kept deliberately lean)

** code_search** extracts the identifiers from a natural-language query and greps the repo (ripgrep, else grep), ranking files by how many of your terms each contains — so the agent reasons about

whereto edit instead of grepping blind, with no model and no index to go stale.

is exact-match, whitespace-tolerant, and

edit_file

rejects any edit that would break Python syntax. Untrusted web/page content is

fenced as data(prompt-injection defense), and the browser bridge refuses any request missing its CSRF header. A token/cost

budget(

COLLIE_MAX_COST

/ COLLIE_MAX_TOTAL_TOKENS

) stops a run at a ceiling.One cross-platform Python codebase — not a per-OS fork. The handful of operations that genuinely differ (kill a process tree on a timeout, secure a token file, convert a path, choose a shell) are isolated in harness/plat.py

, so the same wheel runs everywhere.

OS Status Notes
Linux
✅ native the primary target
macOS
✅ native POSIX; the browser bridge is simplest here (Chrome + Collie on one OS)
Windows
✅ one-click the packaged installer; the agent prefers the file/search tools over bash
WSL2
a Windows-Chrome ↔ WSL bridge uses the LAN IP + wslpath (handled for you)

Collie measures itself against other harnesses on the same task and model — you run it yourself; no numbers are asserted here:

DEEPSEEK_API_KEY=... python swe_run.py --n 5                 # SWE-bench Verified (needs Docker)
python -m bench.multirun_eval                                # pass@1 / pass@k / Wilson CI / McNemar
python -m bench.polyglot_eval --langs python,cpp,javascript  # Aider-Polyglot, multi-language
python -m harness.cli compare --vs all                       # vs Claude Code / Aider / …
  • The benchmark harness is version-tagged and reproducible. "Progress is a number" cuts both ways — Collie surfaces the levers that turn out net-neutral, not just the wins. - Token counts are real usage (the model's own usage

, orharness/apitap.py

metering for CLIs that report none) — apples-to-apples, same source both sides. - Collie draws a personal Max/Pro subscription only through the first-party OAuth path ( anthropic-oauth

), the same mechanism the official CLI uses; it never scrapes or resells subscription tokens. Cheap API keys and local models are the default.

MIT © 2026 — see LICENSE.

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