https://github.com/interesting-vibe-coding/agentshot

📸 The screenshot tool built for AI agents — auto-compress to vision's sweet spot, paste anywhere with up to 81% fewer image tokens, no loss in comprehension. Native macOS, zero deps.
https://github.com/interesting-vibe-coding/agentshot

ai ai-agents claude clipboard gpt llm macos menubar objective-c productivity screenshot token-optimization vision

Last synced: 25 days ago
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📸 The screenshot tool built for AI agents — auto-compress to vision's sweet spot, paste anywhere with up to 81% fewer image tokens, no loss in comprehension. Native macOS, zero deps.

• Host: GitHub
• URL: https://github.com/interesting-vibe-coding/agentshot
• Owner: interesting-vibe-coding
• License: mit
• Created: 2026-06-07T03:58:10.000Z (30 days ago)
• Default Branch: main
• Last Pushed: 2026-06-07T06:07:26.000Z (30 days ago)
• Last Synced: 2026-06-07T06:23:54.129Z (29 days ago)
• Topics: ai, ai-agents, claude, clipboard, gpt, llm, macos, menubar, objective-c, productivity, screenshot, token-optimization, vision
• Language: Python
• Homepage: https://interesting-vibe-coding.github.io/agentshot-site/
• Size: 54.7 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# AgentShot

The screenshot tool built for Codex and GPT vision agents. Snip a region and it's auto-compressed to the vision model's optimal size, then copied to your clipboard.

**Why it matters for Codex:** OpenAI bills vision input by the image's pixel dimensions, tiled. A full-screen Retina grab burns thousands of tokens before the model reads a thing. AgentShot caps the long edge at 1568px and JPEG-encodes it, so you stop paying for pixels the model never uses.

**Measured, not theoretical** — same screenshot, real OpenRouter API calls (`bench/run_openrouter_tokens.py`):

| Model | Original (757 KB, 3024×1964) | AgentShot (174 KB, 1568×1018) | Saved |

|-------|------|------|------|

| **GPT-5.5** | 7083 input tokens | 1896 input tokens | **−73%** |

[中文](README.zh.md)



## Install

```bash

curl -fsSL https://raw.githubusercontent.com/interesting-vibe-coding/agentshot/main/install.sh | bash

```

Installs to `/Applications` and launches. Grant Accessibility once in onboarding. The first capture asks for Screen Recording — allow it, then reopen AgentShot.

## Usage

Press `⌘⇧2` to start. Click once for full screen, or drag to select a region. A preview appears:

- `C` / `↩` — copy the compressed image (label shows `original KB → compressed KB`)

- `⇧C` — copy the original

- `Esc` — cancel

Paste into Codex or any model billed by image resolution. Shortcut, quality tier, and launch-at-login live in the menubar (📸).

## How it works

OpenAI bills vision by pixel area (tiled). AgentShot's pipeline: downscale to ≤1568px long edge → JPEG q0.82 → enforce ≤⅓ the original size → hard cap at 1000 KB. Reading accuracy is unaffected — only token count drops ([benchmarks](bench/RESULTS.md)).

> **Note on Claude:** Anthropic normalizes images server-side before billing, so for Claude the token cost is already fixed regardless of what you send — AgentShot saves no tokens there. The win is real on resolution-billed models (GPT/Codex).

---

Homepage & benchmarks: **https://interesting-vibe-coding.github.io/agentshot-site/** · MIT License · part of [interesting-vibe-coding](https://github.com/interesting-vibe-coding)