dsh-screenshot-feedback-hook-mcp
DeepSeek Harness 的截图反馈——让你的编码代理能够看到它构建的内容
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add dsh-screenshot-feedback-hook-mcp@0.2.1Screenshot Feedback Hook Mcp 以 dsh-screenshot-feedback-hook-mcp 发布，当前版本为 0.2.1。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
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A DeepSeek Harness plugin that lets your agent see the screen it just produced — a web page, an EasyEDA/CAD drawing, any desktop app — and correct itself from what it sees.
It is the dsh half of screenshot-feedback-hook-mcp; the Python package still owns capture and compression (mss + Pillow, Windows/Linux/macOS), and this plugin owns the dsh wiring.
The agent calls take_screenshot and the image arrives in the conversation
A Claude Code hook can only return text, so the best it can do is hand back a file path and hope the agent reads it. dsh has a durable image-attachment service, so a native plugin can commit the screenshot and put a real image block into the conversation — the agent does not have to call anything.
| Path | How the image arrives |
|---|---|
take_screenshot tool | the tool result carries the image block |
| after a tool runs (opt-in) | the screenshot rides the tool result as additional context |
| at the end of a turn (opt-in) | the screenshot is steered/injected into the next step |
v0.1.0-rc.8 or later — every API this plugin uses was verified against that tag.dsh plugin forwards to it.screenshot-feedback-hook-mcp >= 0.3.0 that can run capture --json — it owns capture and compression. Three ways to get one are below. Older releases lack that subcommand; the plugin detects it and names the upgrade.The plugin's only contact with this CLI is the command / args pair in its config (see Configuration): it looks command up on PATH once, and that is all. So pick any of the three below — uv is not a hard dependency, just the default route.
A. Install uv — the default config then works as shipped (recommended)
# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
Nothing else to change: the defaults are command: uvx and args: ['screenshot-feedback-hook-mcp'], and uvx fetches the package from PyPI on demand (the first run needs network).
uv needs no Python of its own — it is a standalone binary that downloads an interpreter when it needs one. That makes this the lowest bar for a machine with no usable Python yet; route B requires you to already have one.
B. You already have Python and want a resident install
pipx install screenshot-feedback-hook-mcp
# or: uv tool install screenshot-feedback-hook-mcp
Then point the config at it. A later layer replaces the whole config, so restate every key you want:
# ~/.dsh/profiles/<name>/cordis.patch.yml
- id: screenshot-feedback
name: dsh-screenshot-feedback-hook-mcp
config:
command: screenshot-feedback-hook-mcp
args: []
monitor: 0
C. Inside a venv, or you would rather not touch PATH at all
Give command an absolute path; the rest is as in B:
command: C:\Users\you\proj\.venv\Scripts\screenshot-feedback-hook-mcp.exe
args: []
command/args/cwdare not on the settings card — they decide where the executable lives, which is a deployment fact rather than a user preference. So routes B and C mean editing the YAML above; there is no control for them in the settings page.The failure messages are actionable, at least: when the command cannot be found the plugin tells you to install uv, or to set
commandtoscreenshot-feedback-hook-mcpwith an emptyargsafter a pipx install; when the Python package is too old it names the upgrade instead of dumping an argparse usage string at you.
This plugin is listed on awesome-dsh-plugin under vision, so you can install it straight from the dsh plugin market. The market card currently hands out the GitHub spec below — the npm spec is waiting on that site's own probe to link the npm package, which is outside this repo. Typing the npm command below yourself has always worked.
dsh plugin --profile web add dsh-screenshot-feedback-hook-mcp
dsh web
Ask the agent to "take a screenshot and tell me what is on screen". Use --profile <name> for whichever profile you boot.
The plugin registry lists a git spec, and it works: pnpm clones the repo, runs this package's prepare script to build lib/, then packs the result and installs that.
dsh plugin --profile web add github:lkh081231/screenshot-feedback-hook-mcp#path:/dsh-plugin
pnpm 10 and later gate build scripts. The first install — before the built package is in pnpm's content-addressable store — can stop with
ERR_PNPM_GIT_DEP_PREPARE_NOT_ALLOWED. Allow it in~/.dsh/profiles/<name>/pnpm-workspace.yamlunderonlyBuiltDependencies, copying the exact entry pnpm's error prints, then run the command again. Once the built package is cached the gate no longer applies.
Do not point dsh plugin add at a working tree. dsh plugin --profile web add ./screenshot-feedback-hook-mcp/dsh-plugin installs the directory as a pnpm link:, and that fails two different ways:
lib/ is a build product and is not in git. pnpm does not run prepare for linked packages, so main: "lib/index.js" points at nothing and dsh dies at boot:
dsh: plugin tree failed to load: ... Cannot find module
'~/.dsh/profiles/web/node_modules/dsh-screenshot-feedback-hook-mcp/lib/index.js'
Building in place fixes that and causes something worse. Node resolves a linked package from its real path, so after npm install the @deepseek-ai/dsh-* copies sitting in dsh-plugin/node_modules/ shadow the host's — the duplicate-instance failure described in Upgrading from 0.1.0, which breaks every tool call in that profile, not just screenshots.
To install from a checkout, pack it first so only the files allowlist reaches the profile:
git clone https://github.com/lkh081231/screenshot-feedback-hook-mcp.git
cd screenshot-feedback-hook-mcp/dsh-plugin
npm install && npm run build && npm pack
dsh plugin --profile web add ./dsh-screenshot-feedback-hook-mcp-0.2.1.tgz
Whichever route you take, confirm ~/.dsh/profiles/<name>/node_modules/@deepseek-ai/ holds no dsh-* package — only schemastery and cosmokit belong there.
For what changed in each release, see the changelog.
0.1.0 installed dsh's runtime packages into the profile as ordinary dependencies, putting a second @deepseek-ai/dsh-tools in front of the one dsh itself loads. The damage is not limited to screenshots — every tool call in that profile dies with:
Cannot read properties of undefined (reading 'prepare')
0.1.1 declares them as peers, so nothing dsh-related is installed into the profile any more. If you already have 0.1.0, clear the polluted node_modules along with it:
dsh plugin --profile web remove dsh-screenshot-feedback-hook-mcp
rm -rf ~/.dsh/profiles/web/node_modules
dsh plugin --profile web add dsh-screenshot-feedback-hook-mcp
Then confirm ~/.dsh/profiles/<name>/node_modules/@deepseek-ai/ holds no dsh-* package at all — only schemastery and cosmokit belong there.
This package is a dsh bundle — an npm package that carries a configuration layer, so you never hand-write a patch. Its package.json declares what it contributes:
{
"name": "dsh-screenshot-feedback-hook-mcp",
"main": "lib/index.js",
"files": ["lib", "cordis.patch.yml"],
"dsh": { "bundle": { "patch": "./cordis.patch.yml" } }
}
That cordis.patch.yml is the layer. It references the plugin module by package name — not by relative path, or Node could not resolve the installed code:
- insert:
- id: screenshot-feedback
name: dsh-screenshot-feedback-hook-mcp
config:
command: uvx
args: ['screenshot-feedback-hook-mcp']
monitor: 0
dsh plugin --profile <name> add ... forwards to pnpm inside the profile directory, sees the dsh.bundle manifest, and appends the package to that profile's dsh.profile.bundles:
{
"name": "dsh-profile-web",
"dependencies": { "dsh-screenshot-feedback-hook-mcp": "..." },
"dsh": { "profile": { "bundles": [
"@deepseek-ai/dsh-base",
"@deepseek-ai/dsh-web-app",
"dsh-screenshot-feedback-hook-mcp"
] } }
}
Inspect the layer before booting anything:
dsh --profile web --dump-config # shows a `# == dsh-screenshot-feedback-hook-mcp` layer with its id: screenshot-feedback row
To uninstall: dsh plugin --profile web remove dsh-screenshot-feedback-hook-mcp drops both the dependency and its layer.
Layers compose in this order: each bundle's patch in dsh.profile.bundles order (@deepseek-ai/dsh-base first) → the profile's own cordis.patch.yml → the home-level $DSH_HOME/cordis.patch.yml → every --patch overlay. So you can override this package's row from your own profile layer without touching the package.
Day to day, tune it from the card at Settings → Plugins → Plugin configuration → Screenshot feedback. It writes $DSH_HOME/settings.yaml, layered over the composition entry, with no restart. Every field on the card says whether you have overridden it and resets back to the composed value in one click.
The bundle inserts one plugin row with id screenshot-feedback — the right place for fixed deployment facts. To change it, add a row with the same id to your profile's $DSH_HOME/profiles/<name>/cordis.patch.yml. A later layer replaces the whole config value, so restate every key you want:
- id: screenshot-feedback
name: dsh-screenshot-feedback-hook-mcp
config:
command: uvx
args: ['screenshot-feedback-hook-mcp']
monitor: 1
autoAfterTools: true
autoAfterToolsDelayMs: 2000
| Field | Default | On the card | Meaning |
|---|---|---|---|
command | uvx | The screenshot executable. Installed with pipx/uv tool? Set it to screenshot-feedback-hook-mcp and clear args. | |
args | ['screenshot-feedback-hook-mcp'] | Fixed arguments placed before the subcommand. | |
cwd | '' | Working directory for the child process; empty means the host's cwd. | |
monitor | 0 | ✓ | 0 stitches every monitor, 1..N picks one. list_monitors shows the indices. |
delayMs | 0 | ✓ | Wait before a manual capture, so a page or drawing finishes rendering. |
maxEdge | 1568 | ✓ | Longest edge in pixels. Do not exceed 2000 — the attachment store refuses larger images. |
targetKb | 80 | ✓ | Byte budget. dsh has no 25k-token MCP output cap, so raise it when you need more detail. |
captureTimeoutMs | 30000 | ✓ | Per-capture timeout, on top of the configured delay. |
warnOnTextOnlyModel | true | ✓ | Explain how to reach an image-capable model when the gate refuses. Once per reason, per session. |
autoAfterTools | false | ✓ | Capture after a matching tool call. |
autoAfterToolsMatcher | edit|write|str_replace_editor | ✓ | Tool names. A plain `[A-Za-z0-9_ |
autoAfterToolsDelayMs | 1500 | ✓ | Wait before the automatic capture. |
autoOnTurnStop | false | ✓ | Capture as a turn is about to close. |
autoOnTurnStopDelayMs | 1500 | ✓ | Wait before the automatic capture. |
autoOnTurnStopSteer | true | ✓ | true steers the model into one more step to look at it; false only injects it as context. |
command / args / cwd are deliberately off the card: they decide where the executable is found, which is deployment composition rather than user preference. Editing config hot-swaps the plugin; editing the card needs not even that — every trigger re-reads the configuration.
dsh's Plugin configuration tab renders the intersection of two ledgers: which settings namespaces the Host serves, and which cards the browser registered under those keys. So this package ships both halves, paired by the single namespace screenshot-feedback:
src/index.ts) registers the namespace through installSettingsSection from @deepseek-ai/dsh-settings, with the cordis.yml row as the composition base, and points its configuration source at the resolved scope. With no settings service mounted it falls back to the composition entry and behaves exactly as before.src/client/) registers a React card into the settings.plugin.item keyed slot under that same namespace. It reads and writes through ctx.settingsScope, which fences each write with the revision it read, so a form that has drifted from the document is refused rather than overwriting a concurrent change.The browser half is discovered through the dsh.client declaration in package.json, and its artifact is lib/client.js:
{
"exports": { "./client": { "default": "./lib/client.js" } },
"dsh": { "client": { "platform": "web", "inject": ["@deepseek-ai/dsh-client-ui-settings-plugins"] } }
}
[!NOTE] dsh's own
clientBundlepreset that produces this artifact is not published to npm (its README lists this as a known limitation), so tsdown.config.ts reproduces the contract here: the lazy-CJS closure factory, thewindow.__ModuleLoader__.loadbanner/footer, and keeping only module-table specifiers asrequire(). When upgrading dsh, re-checkpackages/client/tsdown.client.tsandpackages/client/web/src/platform.tsagainst it.
Both are off by default: each screenshot is an image that rides every later request in the session until compaction.
autoAfterTools hooks tools/post-execute and attaches the screenshot to the tool result. It cannot loop, and it skips failed tool calls (their screen proves nothing).autoOnTurnStop hooks agent/turn-stopping. Steering there forces another step, which reaches the same stop boundary again — dsh's Claude Code hook bridge pins stop_hook_active to false and has no consecutive-block cap, so a naive Stop hook keeps the agent running forever. This plugin dedupes on payload.turn: at most one capture per turn.A failing screenshot never blocks anything — it is logged and the tool pipeline or turn continues unchanged.
Capture itself lives in the Python package, so these apply to every front end it has — this plugin included.
mss is limited; the CLI detects the session and every screenshot carries a warning about it, so the model is told. That warning fires whenever XDG_SESSION_TYPE=wayland, even when XWayland makes the capture come out fine.[!WARNING] A missing macOS permission is not reliably detected. Verify it by hand once.
The current check is an after-the-fact heuristic: it shrinks the frame to 16x16 and looks at the grayscale range, so it only fires when the capture is near-uniform (pure black, a solid-colour wallpaper). A photographic wallpaper does not trip it — and that is what macOS ships with.
So the model can receive a screenshot that looks like a perfectly normal desktop, with no warning attached, while the window it wanted is simply not in it. That is worse than a black screen: the model concludes its own page failed to render and goes off debugging code that is fine.
Before relying on the automatic timings, run the CLI by hand once and look at the image:
uvx screenshot-feedback-hook-mcp capture --out shot.jpgIf your window is in it, the permission is granted and everything below works. A definitive check (
CGPreflightScreenCaptureAccess(), independent of what the frame looks like) is planned but needs a macOS machine to verify.
Environment warnings that do fire reach the model: they ride in the screenshot's warnings and are rendered as a <warnings> line beside the image, so the model sees the reason rather than only a broken picture.
dsh only puts an image into the conversation when the exact route declares image input (ctx.llm.resolveModelInfo(...).inputModalities) — the same gate as the built-in read_image tool. On dsh v0.1.0-rc.8, the built-in deepseek-official route publishes only deepseek-v4-flash and deepseek-v4-pro, and both are text-only.
[!IMPORTANT] The Settings page cannot declare modalities. The model card under Settings → Models only edits
id/ name / context window / max tokens — there is no modality field, so any model you add there is treated as text-only and this plugin refuses to capture. After adding a custom model, click Open config file on that page and add the modality to it by hand insettings.yaml:input: [text, image](orinputModalities: [text, image]underllm-deepseek). Hand-written fields survive later edits made from the Settings page.
To get an image-capable route:
Add an Anthropic/OpenAI-style catalog provider under Settings → Models and pick one of its vision models.
For a custom provider, declare the modality in $DSH_HOME/settings.yaml:
llm-pi-ai:
providers:
my-gateway:
apiKeyEnv: GATEWAY_API_KEY
api: openai-completions
baseURL: https://gateway.example/v1
models:
- id: vision-model
input: [text, image]
Catalog providers use modelOverrides.<model-id>.input instead; a whole route can fall back with defaultInput: [text, image].
If your DeepSeek endpoint really serves a vision model, list it under llm-deepseek.models with inputModalities: [text, image].
These fields assert what your endpoint supports; they do not add capability it lacks.
@deepseek-ai/dsh-mcp-client can run the same Python package as an MCP server, exposing mcp__screenshot__take_screenshot. Same image gate, but no automatic capture.@deepseek-ai/dsh-hooks-claude-code runs an existing hooks.json. Use PostToolUse only, with lowercase dsh tool names in the matcher and --image-tool read_image so the agent is pointed at a tool that exists. Do not use a Stop hook there — stop_hook_active is always false on dsh, so the CLI's loop guard cannot fire.npm install
npm run typecheck
npm test
npm run build
The real-capture integration test is skipped unless you point it at an installed CLI:
DSH_SCREENSHOT_CLI=../.venv/Scripts/screenshot-feedback-hook-mcp.exe npx vitest run
[!WARNING] Every
@deepseek-ai/dsh-*package (and@deepseek-ai/cordis) is a peer dependency, never adependency. Local development gets them fromdevDependencies; at runtime they must come from the host installation. Moving one back intodependenciesmakes pnpm materialize a second copy inside the profile, which shadows the symlinks dsh keeps in~/.dsh/profiles/node_modules/. dsh-tools keys its scheduler with a module-localSymbol, so two copies meanctx.tools[TOOL_RUNTIME_SCHEDULER]isundefinedand every tool call in that profile —read,write,bash, all of them — dies withCannot read properties of undefined (reading 'prepare').tests/packaging.spec.tsguards this.
MIT License.