@mskyurina/dsh-run-watchdog
针对 DeepSeek Harness 长时间运行命令的用途感知监控
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add github:Hirate99/dsh-run-watchdog#184aec0aedc141b153dd00f37d797faa568d17e9Run Watchdog 以 @mskyurina/dsh-run-watchdog 发布，当前版本为 0.1.3。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。
点击下方 Badge 复制 Markdown，粘贴到 README 即可。
验证 package.json 声明的 GitHub 仓库，即可管理这个公开页面。认领后，Hub 会优先安排当前版本的安全扫描，并在通过后公开展示结果。
认领这个 Plugin →English | 简体中文
Monitor long-running DeepSeek Harness jobs using their purpose and live output. Alert the main agent when training, builds, tests, or data processing need attention.
Supports DeepSeek and Jev. Version 0.1.3.
The watchdog catches NaN during training and alerts the agent.
Open Plugins → Add plugin, enter the package name, then select Install → Enable now:
@mskyurina/dsh-run-watchdog
Use @mskyurina/dsh-run-watchdog@<version> to pin a version. Configure it under Plugins → dsh-run-watchdog.
Alternatively, install the v0.1.3 release package, or build a package below. The repository no longer tracks dist; install a release package.
Requires Node.js ≥ 22.19 and DSH native bash / pwsh tools with background job support.
npm ci
npm run check
npm pack
Install the generated mskyurina-dsh-run-watchdog-0.1.3.tgz through Desktop's plugin page. Alternatively, fully quit Desktop and use its bundled CLI on Windows:
& "$env:LOCALAPPDATA/Programs/DeepSeek Harness/resources/runtime/cli/bin/dsh.cmd" plugin --profile desktop add "<absolute-package-path>/mskyurina-dsh-run-watchdog-0.1.3.tgz"
Reopen Desktop and configure the plugin.
Development dependencies are pinned to DSH 0.2.1-alpha.3 and Cordis 4.0.5-alpha.2. Desktop 0.2.0-rc.2's bundled runtime was also tested previously. Rerun integration tests when upgrading the host.
watch_status, without task alerts or stops. Monitoring failures still notify the agent. Set recordPath to save decisions.Save changes before selecting Test connection. Changes apply to newly attached monitors.
| Setting | Default | Description |
|---|---|---|
firstCheckMs | 10000 | Delay before the first check |
judgeTimeoutMs | 8000 | Model request timeout |
stopThreshold | 0.8 | Jev probability threshold for automatic stopping |
allowAutoStop | false | Allow individual jobs to request automatic stopping |
recordPath | Unset | Local JSONL decision log |
Requests include the task purpose, command, and up to 16000 characters of recent output. Local records contain the same evidence. Credentials are resolved from DSH first, then from the environment variable named by apiKeyEnv.
The plugin supplies instructions to the main agent. The agent starts a native background job and attaches watch_job; users do not need to name tools or provide tool parameters.
Attachment returns immediately. Jobs are monitored concurrently with independent log cursors. Monitoring does not consume the agent's output, start commands, or restart jobs. The agent can read further output with job_output.
Each check selects an action (continue, notify, recommend stopping, or uncertain) and a separate next check interval (10, 30, 60, 120, 300, or 600 seconds). Alerts do not end monitoring. The judge continues to choose the interval after an alert. Repeated attention decisions are suppressed until a successful continue decision re-arms notifications.
stopThreshold, and both deployment settings and the job authorize stopping. Missing output or unreadable sources prevent automatic stopping. This score is not a calibrated accuracy estimate.Output redirection is supported. Pass up to eight absolute file paths in log_paths when attaching. The monitor reads these files incrementally alongside job output and reports missing files, read failures, truncation and rotation. Quiet output is not a task failure; missing evidence is not proof of health.
watch_job returns output sources, mode, health and first check time. watch_status(jobId) exposes the latest judgment and input evidence, consecutive failures and next check time. Two consecutive judge failures notify the agent; recovery sends another notification. Unexpected observation-loop failures are also reported. Jev supplies choices and scores without an explanation; DeepSeek can supply a short explanation. The main agent should explain monitoring startup, task problems and lost visibility to the user.
Normal completion uses native DSH notifications. An alert cancels job_output(wait=true) waits in the same session, including waits started while an alert is pending. This does not cancel the agent or stop jobs. Other blocking tools are not interrupted.
Monitoring ends when the job finishes or the plugin unloads. Unloading does not stop jobs; restarting the plugin does not restore monitors. The last 100 ended monitors remain queryable in memory. Failed model requests retry with bounded backoff.
npm run check
Runs the build, type checks, and offline regression tests without API keys. Coverage includes decision thresholds, chunked and truncated logs, immutable state, scheduling boundaries, continued checks after alerts, monitoring failure and recovery, log rotation, concurrent jobs, wait interruption races, DSH tools, and real child processes.
Online connection tests call the selected provider:
npm run smoke -- jev
npm run smoke -- deepseek
Set WATCHDOG_MODEL to override the test model. Offline tests do not establish model quality across real tasks, and the demo does not guarantee consistent autonomous tool selection.
| File | Responsibility |
|---|---|
src/output.ts | Pure log accumulation and evidence statistics |
src/decision.ts | Model input, action selection, and comparison rules |
src/monitor-state.ts | Pure check snapshots and scheduling |
src/monitor.ts | Log reads, model requests, and the monitoring loop |
src/jobs.ts | DSH job access and independent cursors |
src/interrupt-wait.ts | Release output waits when alerts arrive |
src/index.ts | Tool registration, alert delivery, and Cordis lifecycle |
src/providers.ts | DeepSeek / Jev request adapters |
src/settings.ts, src/client.tsx | Credentials, connection tests, and settings UI |
docs/ and .integration/ contain local verification artifacts and are excluded from version control. README demo assets live in assets/.
Reusable online evaluations live in test/evaluation/ and require explicitly configured judge credentials. Temporary host probes, diagnostic scripts and raw evaluation records stay in the ignored .integration/ directory.
Pushes to main and pull requests run the full checks and pack on Windows and Linux. The prepack hook builds dist for npm pack and npm publish. Git keeps source; the npm package contains the runtime artifacts and needs no install-time build.
For a new release, run npm version patch --no-git-tag-version (or specify a version), commit, and push main. After both platforms pass, the workflow creates v<version>, publishes to npm, and creates a GitHub Release. Later commits with the same version do not publish again. Rerun the original workflow to resume missing publication steps; existing tags are never moved.
Like agent-workspace, publishing uses npm Trusted Publishing. Authorize GitHub owner Hirate99, repository dsh-run-watchdog, workflow ci.yml, and environment npm in this package's npm settings, with direct publishing enabled. Trust is package-specific; another package's authorization does not transfer. No npm token is required. After the initial publication, configure this trust on npm to enable subsequent workflow releases.