Plugins

DeepSeek Harness (dsh) plugin that bridges the local 'Screen Automation Helper' desktop platform (Windows/macOS) into the Agent tool system. Exposes status, capabilities, workflow list/run/stop, run management, screen capture, local recognition primitives

Local, auditable personal memory for DeepSeek Harness: preferences, project conventions, workflows and error lessons persisted as a changelogged JSON file in the workspace, with onboarding, auto project-convention extraction and evidence-backed lessons.

A local-first, human-gated authorial film workflow for DeepSeek Harness

Conventional-commit enforcement, changelog generation, PR summaries and branch pushes through the plain git CLI.

A project-agnostic multi-agent collaboration protocol for the DeepSeek Harness: loop guards that stop runaway agent loops, a six-field handoff format, risk-tiered review routing, and a fixed verify→commit→push→review→close sequence. One skill instead of the same rules copy-pasted into every agent's instructions.

Cordis-native, evidence-driven full-stack engineering workflow: inspect-first planning, explicit verification evidence, and approval-aware gating for sensitive operations.

Contract-drafting agent preset: 11-stage lawyer workflow with 5-way parallel AI review, decision gates, and domain packs for general, employment and equity-investment contracts.

Connects DSH to local Beav for Xiaohongshu (RED/RedNote) and social-media AI operations: topic research, knowledge, copywriting, image, audio, and short-video workflows with approval and artifact tracking.

Adds dangerous-operation policy checks, output redaction, and a security-review workflow.

Plugin diet and compatibility diagnostics for DeepSeek Harness: scans context cost and plugin/runtime/profile conflicts, then applies low-risk reversible trims only after confirmation; ships a Web settings console.

Make your dsh ready for serious coding. (Tools x Schemas)^REPL. `skill://`, `ctx://`, `agent://`, `dvc://`, `dsh://`, IPython REPL, Context as Variables, cross compactions recallable, full context revive. `hash-edit`, `dvc://browser`, subagent as function, workflow as function.

Adapts Easy Ask AI Skill's Prompt Ready and Get Clear flows to Harness chats with a native sidebar; the original Skill can be installed in other compatible Agents.

Workflow blueprint planner for DeepSeek Harness: turns a business goal into validated steps, capabilities, permissions, failure handling, acceptance criteria and rollback, then exports Markdown or JSON.

Single-cell RNA-seq workbench usable from the Harness UI or from agent tools: imports h5ad, 10x, loom, Seurat RDS and archive files, runs QC, filtering, normalisation, highly variable genes, PCA, neighbour graph, clustering, UMAP/t-SNE, marker genes and cell-type annotation, offers resolution scans and saved marker panels, and exports h5ad, result tables and reports.

Document-driven workflow plugin for DeepSeek Harness: verified index, clarification gates, notes & plan, live sidebar panel.

Blocks risky tool-call shapes before execution: inline multi-line Python, forwarded content without a source, missing source labels, and memory writes past the character cap. It also asks for confirmation before shell commands, and one rule is specific to the author's WeChat sending workflow.

Long-form fiction workflow for DSH: seven queryable bibles, edit-impact tracking, living relationship and plot maps, and a first-chapter tryout that picks your writer. Its /novel-panel routes, including save, archive and reconcile, are mounted with webServer.register and carry no DSH Host/Origin admission check, so a web page open in your browser can write to the novel project through them.

Research-style problem solving in four gated stages: record sources by retrieval tier with local before web, turn each shortfall of existing tools into a gap that needs evidence, score candidates against weighted metrics with a deterministic engine, fuse or improve the weak ones, then iterate on measured deltas. Also organizes a directory into human-facing and machine-facing trees.

Registers 25 software engineering workflow skills covering spec, planning, build, test, review and ship. Mirrored from addyosmani/agent-skills (MIT).

Writes engineering decisions down the way DSH documents its own — every non-trivial change leaves a Markdown note under .agents/notes/<lifecycle>/<class>/ holding the problem, the decision, the rejected alternatives and the consequences, committed to git and reviewable like code. It supplies the workflow for that: five tools (note_search, note_read, note_write, note_verify, note_skip), an end-of-turn hook that asks a code-changing turn to either write a note or record an explicit skip, the tree/format/archived checks, and the write-notes-like-deepseek skill bundled in the package and mounted by the plugin. A sidebar board that renders the notes into four views (architecture baseline, timeline, rejected proposals, decision list) comes with it; the notes themselves stay plain Markdown.

Seal proven command chains into reusable executable tool scripts for DSH agents. DSH 代码脚本固存，留住模型成功自实现的工作流。

Manage iterative text annotation through DSH tools with rule versions, stale-result isolation, human review preservation and traceable exports; requires a separately installed Python backend.

Multi-workspace agent federation with persistent ticket trees, parallel worker sessions, structured evidence reports, independent acceptance checks, retry/stop and restart recovery. Workers get shell and file tools in the ticket's directory, company_verify re-runs the ticket's acceptance commands in a shell on the host, and scope lists are task authorization rather than a sandbox. State is stored in ~/.dsh/ai-company; the optional company_repo_* tools run separately installed aoci/codegraph commands on any path they are given.

Anthony Fu's agent workflow for DeepSeek Harness: issue triage, digest, task execution, PR creation and simplification