플러그인

DeepSeek Harness용 Git 인식 쓰기 보호 플러그인: 사용자의 커밋되지 않은 변경 사항을 덮어쓸 전체 파일 쓰기를 차단하고, 턴 종료 시 보호된 파일에 어떤 일이 있었는지 보고

Lets the model trigger compaction itself at a safe point via a compact_now tool (works mid-turn), plus a context_status tool reporting real token usage against the session's actual context window.

中瑞世联工作台 / CRWU audit workbench for DeepSeek Harness: pick a pending audit report, dispatch one AI audit subagent, watch and stop/restart it, auto-upload deliverables to Aliyun OSS.

Verified restart for DeepSeek Harness: restart without privileges, check that the harness really came back, report the verdict to the session that asked, and hand back what was left to do.

A newspaper-style front page for a session you left running, as a Conversation View tab beside Chat and Trajectory: a per-turn timeline (duration, steps, tools, tokens, outcome), file churn counted per file, where the wall clock went and how much of it was the model rather than tools, which single turn ate the spend, failures nobody retried quoted with their failing command, and a context-pressure gauge measured against the routed model's own declared capacity. The briefing is folded from the durable session log and never generated by a model, so it costs no tokens, cannot hallucinate, and is byte-identical for the same log and clock; it appends nothing to the session and reaches no model, and it reports a pending approval without ever answering it. Pages are offered only when they have content, and the tab refreshes itself on turn settle and on a two-speed poll backed by a metadata-only tail probe.

Adds a whole-corpus usage statistics page to DSH with daily and cumulative tokens, cache hit rate, per-model breakdown and a year-long activity heatmap, all read from the provider-reported usage.

Routes eight DSH lifecycle events through dedup, quiet hours and digest batching into seven channels. Severity maps to the fields Bark, ntfy, Telegram and webhooks actually support; failed deliveries retry with jittered backoff and survive a restart; per-channel circuit breakers stop hammering a dead endpoint; and a self-check reports a degraded relay instead of going silent.

Registers the Zemingxingxiao five-element brand-diagnosis skill with five companion reference skills (theory, diagnosis playbook, 240-case library, visual templates, glossary), a system-prompt router, and the mandatory HTML report template with 13 theory diagrams.

Fixes the Windows workspace-open action. The shipped opener runs `explorer.exe "<file:// URI>"`, which on some hosts reports success without raising a window — the exit-code verdict cannot tell an opened window from nothing happening. This routes that one action to `explorer.exe /e,<dir>`, which raises a window reliably, and leaves every other application in the menu on the shipped path.

Shared infrastructure for data assetization plugins: business rules loader, file format adapter, report generator, path validator, audit logger Also known as @deepseek-ai/dsh-data-asset-shared.

Tracks API token usage and estimated costs with per-route model pricing, optional billing groups, synchronized CNY/USD display, session reports, composer totals and a clickable daily sidebar total.

Host- and agent-layer DeepSeek Harness plugin that prices every automatic context rewrite before it lands, asks the human by default, and reports what the provider had to re-read cold.

Long-term memory for DeepSeek Harness, read-only as of 0.1.0: a scribe_recall tool that reads a plain-markdown memory room, path rules that refuse directory traversal, Unicode smuggling and NTFS alternate data streams, and a bounded index whose truncation is always reported rather than silent.

Rapid-refill circuit breaker for DeepSeek Harness automatic compaction. It refuses a compaction that would be futile — the context refilled within fewer than N tool turns M times in a row, which the unbounded step-pressure trigger cannot detect — and instead of burning a summarization call on every step it reports the situation with advice, usually that a single read or tool output was too large. Shows state and re-arms through /compaction-breaker, and injects one prompt section so the model relays it to the user. Covers host-plane sessions through its profile bundle; ordinary sessions need one row replaced inside an agent preset.

Adds a sidebar panel to the DeepSeek Harness web UI that reports token usage and cost straight from DeepSeek's own usage API (today's spend, 7/30-day trends, today's hourly split, a history table, cost breakdown, peak/off-peak tier pricing), plus per-session detail from local logs. Zero-config: it reads the browser sign-in for the official figures, and falls back to local session logs with the source labelled.

Live progress for long-running DSH tasks: a script appends JSON lines to a per-session progress file, the Web UI draws them in a floating overlay and a right-sidebar tab that also lists background jobs which reported nothing, and `dsh-progress run -- <cmd>` wraps a command that cannot report for itself.

Deterministic session evidence reports for DeepSeek Harness: /transcript writes styled single-file HTML / Markdown / JSON reports from canonical session logs, /stats prints a terminal stats card, /archive writes per-session ZIPs

Speaks your agent's reports in a voice you choose, compressing long reports before speaking. Character voices need no training - a 3-10 second reference clip clones one, and community-trained models work too - and no 6.4 GB GPT-SoVITS install: the plugin installs its own runtime and voice. An existing GPT-SoVITS can be used instead, and it is the same voice model.

Sidebar card that prices this session's tokens in RMB at official peak/off-peak rates and splits context share by source, with per-turn pricing and a Markdown/CSV history report.

Expose every model already configured in your local DeepSeek Harness to the LAN over OpenAI- and Anthropic-compatible endpoints, with API keys, per-key rate limits, a circuit breaker, model filters and usage reports.

Audits a DSH profile for capabilities nothing consumes: inventories the declared composition rows, counts how often each registered tool and skill is actually called in the session logs, separates calls that were made from calls that returned a result, and reports the ones with no observed consumer. Ships a skill that fixes the evidence-chain format for completion claims.

Collects and redacts DSH runtime diagnostics before filing structured issues in GitHub or Gitea.

Bridge a Feishu bot to a DSH session: open a real session in a workspace, run tasks with the existing model and plugins, and report results back.

Agent screen capture on macOS and Windows: one tool captures the screen and returns the image itself, so the model sees it without a second call. On Windows a whole burst runs in one engine call; on macOS a resident helper drops a region capture to 13ms and a change check to 23ms. A second tool, macOS only, reports whether Screen Recording is granted and opens the settings pane that fixes it.