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A practical operating manual for building, evaluating, securing, and shipping modern LLM agent systems. Modern agents are not "a prompt + a tool."
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@oxbshwVideo & Audio
Plugin
watch-skill
Give AI agents eyes, ears, and verifiable results.
Plugin Signal74/100Solid
maintained99
capable53
documented75
adopted57
Install on Claude Code
> /plugin marketplace add oxbshw/watch-skill> /plugin install watch-skill@watch-skill
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70
Forks
Active
Maintenance
Python
Language
MIT
License
3d ago
Last commit
3mo ago
Created
2h ago
Added
What's inside
Skill(10 skills)
/asking-with-evidenceThe user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Use this to answer from the persistent index with timestamped evidence and a confidence score/configuring-visionThe 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/extracting-structureThe user wants structure pulled out of a watched video — "make chapters for this video", "where does the bug appear in this recording", "turn this screen recording into a bug report", "how strong is my intro/hook". Use this for deterministic extraction from the index — chapters
MCP(1 mcp)
README
Watch Skill · DeepWatch
Give AI agents eyes, ears, and verifiable results.
Watch Skill turns video, audio and screen activity into searchable, timestamped evidence, and answers did that actually work? with a deterministic contract rather than a model's opinion. Add it to the agent you already use over MCP.
DeepWatch is a ready-made agent workspace, built on the official DeepSeek Harness with Watch Skill already composed in, where a tool call leaves a receipt you can open and a result can be checked by something other than the agent that produced it.
Python · PyPI
Node · npm
Gates and directories
Install · Use it · THE LOOP · Packages · Architecture · Docs · Community
Two capabilities, and they work apart
Perception. Video, audio and screen activity become frames, transcripts and OCR text, each carrying an absolute timestamp. Index a source once and query it for as long as you keep it; every answer cites a moment you can open.
Verification. A frozen contract — file digests, JSON values, SQL results,
HTTP responses, DOM state — is evaluated by a separate process. The verdict is
VERIFIED, FAILED, UNVERIFIED or INCONCLUSIVE, and it does not come from
a language model.
Either is useful on its own, and the split is deliberate.
Watch Skill — the engine
Index a recording once and ask it questions for as long as you keep it. Answers cite timestamps you can open. Verification contracts check file digests, JSON values, SQL results, HTTP responses and DOM state, and report passed, failed, unverified or inconclusive — four answers, because three of them are not the same as "no".
Any agent can use it: MCP, a CLI, or a REST API.
DeepWatch — the workspace
Built on the official DeepSeek Harness, with Watch Skill composed in, installed by one command. You get an agent that can see and prove, without wiring anything together yourself.
Every tool call leaves a receipt naming what it touched. Every path a tool declares is checked against one workspace boundary, so a tool cannot quietly write outside it. Results carry a Core verdict you can open, and the Library keeps them after a restart.
Runs in your browser. Compare puts two runs of the same contract side by side and shows where their verdicts diverged.
Watch Skill sees and proves. DeepWatch is the workspace it comes built into.
Start here
Three entry paths. Pick the row that describes you.
| You have | You want | Go to |
|---|---|---|
| An agent already (Claude Code, Cursor, Codex, any MCP client) | Give it eyes, ears and verification | Watch Skill |
| Nothing yet | The whole workspace, agent included | DeepWatch |
| A DeepSeek Harness you already run | Add Watch to it, keep your setup | @deepwatch/dsh-bundle |
1. Add Watch Skill to an agent you already use
pip install 'watch-skill[standard]' # frames, retrieval and the MCP server
watch-skill doctor # checks, and repairs what it can
watch-skill watch <video-url-or-file>
watch-skill ask <id> "what changed at 3:12?"
Take the extra seriously. A bare pip install watch-skill gives you the
CLI, the verifier and the Bridge, and it cannot extract a frame: watch stops
at perceive.missing_dependency on the first video. [standard] is frames,
retrieval and MCP; add [ocr] to read on-screen text, [whisper] for local
transcription when a source has no captions, [loop] for the browser, or take
[all]. watch-skill doctor names the exact command for whatever is missing.
Wire it into any MCP client — [standard] includes the server:
watch-skill serve # stdio MCP server, 39 tools
Or install the skills into 25+ agents at once:
npx skills add oxbshw/watch-skill -g
Every supported client, and how far each is verified →
2. The whole workspace
Prerequisites. Node ^22.19 || >=24, which is what the CLI's engines
declares. Python 3.11, 3.12 or 3.13 — the versions CI runs and the classifiers
list — and only if you want the perception and verification engine. DeepWatch
starts without it and reports every Watch capability as unavailable until it is
there.
# 1. the engine that sees and proves (optional, but it is the point)
pip install 'watch-skill[standard,ocr]'
# 2. the workspace
npm install -g @deepwatch/cli
deepwatch doctor # what is present, what is missing, how to fix it
deepwatch setup # builds the runtime; shows the download and asks first
# 3. a workspace directory to work in
mkdir my-project
deepwatch web --workspace ./my-project
deepwatch web prints a local URL and opens the workspace there. This is the
first thing you see:
Two numbers rather than one fraction, because "installed" and "proved" are different facts and a single percentage would blur them. Ready now counts what has passed a runtime gate. Needs setup counts what has not been configured or not been tested — saved is never presented as tested. You can open the workspace without a provider: the Library, the index and the Watch tools all work locally.
Without a global install, the same package through npx:
npx --yes @deepwatch/cli setup
mkdir my-project
npx --yes @deepwatch/cli web --workspace ./my-project
npx is a way of running @deepwatch/cli, not a different package — there is
no unscoped deepwatch on npm.
What setup downloads. The pinned DeepSeek Harness, its exact required
peers, and the DeepWatch packages at this release's version, into a runtime
under your DeepWatch home. It prints the registry, the versions and the
destination and stops for your agreement; --yes agrees in advance and
--offline refuses outright. Nothing is installed globally except the CLI you
installed yourself. --artifacts <dir> takes the DeepWatch packages from
verified local tarballs this product hashes itself instead of from the registry,
which is what a checkout build wants. It does not make the install offline: the
pinned Harness and its generated peer closure are fetched from npm in that mode
too, and the plan setup prints says so before it fetches anything.
A model provider is not required to start. The workspace boots, the Library works and Watch tools answer without one. You need a provider for the agent — chat, tool use, and the critique step of THE LOOP.
Connect a model, and prove the connection
Four steps in the workspace itself, in this order. The last one is the point.
| In the app | What it does |
|---|---|
| Settings → Models → Add provider | Names a provider and takes a key, or leaves the field blank and reads one from the launch environment. |
| Settings → Role Bindings → Choose a model | Binds a specific provider and model to a role — Chat, or Visual perception. |
| Run provider test | Sends one real request to that exact binding and reports what came back. |
| Ready | Only now will the workspace send anything to it. |
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View @oxbshw’s profile@oxbshwFAQ
watch-skill is a Claude Code plugin with 10 hand-picked skills, indexed on Flowy in the Video & Audio category. Install it with the command on its page. It includes asking-with-evidence, configuring-vision, extracting-structure. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
- What is watch-skill?
- Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence, and answers did that actually work? with a deterministic contract rather than a model's opinion.
- How do I install watch-skill?
- Run these in Claude Code: /plugin marketplace add oxbshw/watch-skill then /plugin install watch-skill@watch-skill. Then prompt normally.
- Does watch-skill auto-invoke its skills?
- Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
- Is watch-skill free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.
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