configuring-vision — Claude Code skill: what it does, how to install
Configures vision providers for Watch Skill: connects OpenAI, Anthropic, Gemini, OpenRouter, or local Ollama without locking to a single vendor.
npx skills add oxbshw/watch-skill --skill configuring-vision -a claude-codeWhat configuring-vision does
The skill configures the visual engine of Watch Skill via the watch-skill setup-vision CLI tool. It supports Anthropic, OpenAI, Gemini, OpenRouter, and local Ollama instances. API keys do not need to be shared in chat sessions: keys can be supplied via environment variables or run directly in the terminal.
Processing tasks can be split across model tiers. You can use a budget model for bulk scene descriptions with --cheap-model and a stronger model for loop critiques with --strong-model. Adding --verify triggers a live probe call, returning a structured error and its fix property if the check fails.
Running without any visual API remains fully functional. Watch Skill still downloads video, reads captions, runs local transcription, and processes OCR, so indexed evidence search works without guessing.
What it helps with
- connect Anthropic, OpenAI, Gemini, or OpenRouter backends to Watch Skill
- configure local vision processing with Ollama
- split video analysis across cheap and strong model tiers
- test vision provider credentials using the
--verifyprobe
Example prompts for the agent
- Configure Watch Skill to use local Ollama for visual analysis
- Set up OpenRouter vision in Watch Skill with separate cheap and strong models
- Verify the Anthropic vision configuration with a test call
How to install configuring-vision
1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill configuring-vision -a claude-code2Manually: put the files in place
~/.claude/skills/configuring-vision/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/configuring-vision/
1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill configuring-vision -a codex2Manually: put the files in place
.agents/skills/configuring-vision/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill configuring-vision -a cursor2Manually: put the files in place
.cursor/skills/configuring-vision/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install oxbshw/watch-skill configuring-vision2Manually: put the files in place
.github/skills/configuring-vision/SKILL.md1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill configuring-vision -a gemini-cli2Platform CLI
gemini skills install https://github.com/oxbshw/watch-skill --path skills/configuring-visionManually: put the files in place
.devin/skills/configuring-vision/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill configuring-vision -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about configuring-vision
How to install configuring-vision in Claude Code?
Run npx skills add oxbshw/watch-skill --skill configuring-vision -a claude-code.
What does configuring-vision do?
It configures the model backend for Watch Skill, routing video frame analysis to cloud providers or local Ollama.
Can Watch Skill work without an active vision provider?
Yes. Without an API key, it still captures video, reads captions, executes local transcription and OCR, and indexes evidence by timestamps.
Source text
SKILL.md · MIT
--- name: configuring-vision version: "1.4.3" description: The user wants to connect an LLM or vision provider, already has an API key, asks "can I use OpenAI/Anthropic/Gemini/OpenRouter", wants local Ollama, or needs different cheap and strong models. Use this to configure provider-neutral visual understanding without tying Watch Skill to one agent or model vendor. license: MIT user-invocable: true allowed-tools: Bash, Read --- # Configuring vision Watch Skill's agent surface and model backend are separate choices. Claude Code, Codex, Cursor, OpenClaw, framework agents, and REST clients all call the same engine; the engine can send selected frames to any supported vision provider. ## Supported providers ```bash watch-skill setup-vision --provider anthropic --api-key <KEY> watch-skill setup-vision --provider openai --api-key <KEY> watch-skill setup-vision --provider gemini --api-key <KEY> watch-skill setup-vision --provider openrouter --api-key <KEY> watch-skill setup-vision --provider ollama ``` Prefer a key the user already has. Do not claim Ollama is required, and do not ask the user to reveal a secret in chat. They can set the matching environment variable or run the command privately in their terminal. ## Route bulk work and verification separately One model can serve both tiers: ```bash watch-skill setup-vision --provider openai --api-key <KEY> --model <vision-model> ``` Or use a cheaper model for scene descriptions and a stronger model for uncertain answers and loop critiques: ```bash watch-skill setup-vision --provider openrouter --api-key <KEY> \ --cheap-model <fast-vision-model> --strong-model <strong-vision-model> ``` Add `--verify` to make one live probe call. If it fails, report the structured error and its `fix`; never echo the key. ## No provider is also valid Without a vision API, Watch Skill still acquires video, reads captions, runs local transcription and OCR, indexes evidence, and searches it. Visual synthesis degrades to timestamped evidence instead of guessing.
© oxbshw · MIT · oxbshw/watch-skill