Harness setup

Where a pasted image ends up differs per harness, and vision takes a different route in each. recover-paste detects which harness it runs inside (process ancestry, then environment fingerprints) and reads only that harness's storage.

Codex

Pasted images become real temp files, and the message carries a tag like <image name=[Image #1] path="/tmp/xxxx.png">. The skill reads the path out of the tag. recover-paste detects Codex and refuses, pointing back at the tag.

One catch with text-only models: once models.json declares input_modalities: ["text"], the Codex TUI blocks Ctrl+V paste outright. Drag the file into the terminal, type its path, or use codex exec -i image.png "...".

Claude Code, Pi, OpenCode

None of them hands the model a usable temp-file path the way Codex does (newer Claude Code builds do write pastes to their own ~/.claude/image-cache/, injected as a path line only in the terminal entrypoint), but all three persist the user message locally before any gateway strips it:

Harness	Storage	Notes
Claude Code	~/.claude/projects/<slug>/<session>.jsonl	images as base64. The injected CLAUDE_CODE_SESSION_ID targets the exact session
Pi	~/.pi/agent/sessions/--<encoded-cwd>--/*.jsonl	same shape as Claude Code
OpenCode	~/.local/share/opencode/opencode.db	SQLite, images as data URLs (read via node:sqlite)

Running a text-only model behind ANTHROPIC_BASE_URL in Claude Code, a pasted image arrives as a pathless [Unsupported Image] placeholder (on lenient gateways) or breaks the request outright (#62009). The bytes are not gone, and that is what recover-paste retrieves.

Skill locations

Harness	Reads skills from
Claude Code	~/.claude/skills/
Codex	~/.codex/skills/
Pi, OpenCode	~/.agents/skills/

Symlinks work in all of them, so linking the skill folder once keeps every agent on the latest version.

Platform support

macOS and Linux are fully supported and verified in CI on Node 22 and 24.

Windows runs the same CI matrix. Detection there skips the process-ancestry pass, since there is no ps, and falls back to the environment fingerprints above, so a harness that sets none of them reads as undetected (force it with --harness or VISION_HARNESS). OpenCode paste recovery is covered on Windows, including the path-separator normalization from #11: opencode records session.directory with forward slashes while path.resolve returns backslashes there, and both sides are normalized before matching. The JSONL stores (Claude Code, Pi) key off os.homedir() and each harness's own on-disk slug, and are exercised on POSIX. External engines (Antigravity CLI, the Claude CLI) run only where they ship a Windows build.

Gateway setups

OpenCode with DeepSeek: opencode auth login, pick DeepSeek and paste the key (it lands in ~/.local/share/opencode/auth.json), then set the default model in ~/.config/opencode/opencode.jsonc to deepseek/deepseek-v4-flash. Pi reads its key from ~/.pi/agent/auth.json.

DeepSeek Harness (dsh)

dsh is different from the other harnesses: vision plugs in as a native tool, not a prompt-triggered skill. The package itself is a dsh bundle, so one command installs it into a profile:

npx -y @deepseek-ai/dsh plugin --profile web add @jasonjin06/vision@latest

This registers a read_image tool whose schema reaches the model on every request (no trigger heuristics), runs the vision CLI shipped inside the same package, and returns the structured evidence as the tool's canonical JSON output. Engines, reuse grants, and guard rules stay in ~/.vision/config.json, shared with every other harness. dsh is in developer preview and its plugin surface may change; the plugin keeps its touch small (raw tool registration, the llm adapter surface for the vision variants, the attachment reader, and one agent pre-step hook) and degrades loudly if any of them moves.