Plugins

Role-based multi-agent team for DeepSeek Harness. The /team command assembles up to 12 specialist subagents (product, architect, researcher, UI, backend, frontend, database, security, reviewer, QA, DevOps, docs) and runs a nine-phase gated pipeline (clarify, research, design, spec review, plan approval, implement, review, test, deliver) over a shared workspace of artifacts (SPEC, PLAN, TASKS, STATE, REVIEW, TEST). Quality gates are enforced by plugin code rather than requested in prompts: an unfinished task cannot be marked completed, quality findings must be adjudicated by the reviewer or QA role, and coverage gaps or rework over budget appear live in the overlay and in /team status. Ships a live team overlay (phases, roster with per-role models, task DAG, artifact preview, decision buttons), a persistent-team mode that resumes across sessions, and per-run token and time accounting. Zero runtime dependencies, no build step.

会话记忆 → OKF 知识沉淀插件:预测驱动的神经自我学习记忆系统。把会话中高价值内容按 OKF v0.1 规范沉淀为长期记忆,跨会话自动唤起。Session-to-OKF memory plugin with neuro-self-learning (predictive recall, uncertainty-driven capture, reinforcement feedback).

Unit conversion toolbox covering 20 categories — length, mass, temperature, area, volume (incl. US cooking units), speed, time, data sizes (decimal MB vs binary MiB), data transfer rates (Mbps vs MB/s), acceleration incl. g-force, illumination (lux / foot-candle), pressure, energy, angle, frequency, power incl. three horsepower definitions, force, torque, typography (px/pt/em/rem), and fuel economy (mpg ↔ L/100km). Two tools — convert_unit and list_units — zero runtime dependencies, pure arithmetic; each result includes the formula applied.

Guarda de disciplina do agente para DeepSeek Harness: quatro portões aplicados na fronteira do harness — disjuntor de loop, fusível de custo de tokens, aviso de troca de rota, aprovação de plano — onde lembretes no nível do prompt não chegam, para que um agente não possa mais queimar uma cota semanal em minutos; chip 🛡 de um clique, limites recarregáveis a quente e predefinições de invisível-mas-blindado a apenas aviso.

Ferramentas Odoo só de leitura sobre JSON-RPC: informação do servidor, introspeção de campos de modelos, e um search_read restrito limitado a uma lista de modelos permitidos cujos nomes de campos de domínio não podem conter pontos, pelo que não é possível percorrer registos relacionados. Uma ferramenta de criação de rascunhos só é registada quando allowWrite está ativado, e limita-se a sale.order e project.task com o estado de rascunho imposto pelo plugin.

Adiciona controles de sessão, de projeto e globais na interface web do DSH para habilidades, servidores MCP, ferramentas, injeções de prompt, escalonamento de aprovação e salvaguardas; a aplicação é limitada ao agente atual.

Portão de verificação para agentes DSH: cada critério de aceitação deve ser respaldado por evidência real de ferramentas carimbada pelo servidor antes que o portão de conclusão deixe um objetivo passar (auditoria consultiva, portão de aplicação, permissões duráveis).

Imposição de conventional commits, geração de changelog, resumos de PR e push de branches através da CLI simples do git.

Disciplina de desenvolvimento guiada por especificação para dsh: cinco skills keel (anchor/spec/probe/build/audit), três ferramentas de revisão e seis modelos de spec impõem spec antes de código, verificação de suposições e controle de escopo.

Plugin de imposição do protocolo de memória: faz a ponte com o servidor MCP opencode-memory, força memory_weave antes das chamadas de ferramenta, ingere automaticamente as interações e injeta contexto de memória nas etapas do agente.

Model-callable compact_agents tool that force-compacts context in every live session (main session, ordinary sub-agents and AgentTeams members alike), queues busy targets and compacts them when the turn ends, reports the shadowed node count and estimated tokens per target, and ships a browser form for the trigger ratio, retained ratio, controlled-phase output budget, auto-continue budget and an end-of-turn pre-compaction ratio that compacts near the trigger line once a turn ends, so a reply no longer opens with a wait for the summarizer.

DeepSeek Harness plugin for Agent-Playbook: multi-agent claims, isolated git worktrees, and enforced acceptance checks. "Done" is an exit code, not a claim.

Connects DeepSeek Harness to a local SiYuan (思源笔记) desktop app: registers its note tools as mcp__siyuan__<tool>, exposes the AI configured in SiYuan together with its agent loop as one more tool, ships a notes skill, and enforces a readonly/authoring/full profile on every call while keeping the tool list available when the app is closed.

Team cost captain: meters every model call (subagents included), attributes each call to a member by workspace rules, prices it with the built-in DeepSeek 2026-09 catalog (peak/off-peak, CNY/USD) or user overrides, and appends it to a local JSONL ledger. Adds hot-reloadable member budgets, 80%/100% webhook alerts, optional over-budget enforcement, a team_cost_report tool with CSV export, and a settings-page team dashboard served over a Typert RPC service.

Open folders on remote hosts over SSH as Harness workspaces: file tools (read/write/edit/grep/glob) and shell commands run directly on the remote host over SFTP, ripgrep, and ssh2 exec, with no local mirroring, an encrypted multi-host registry, and the local sandbox policy still enforced.

AST-based context compression, test log filtering, and token budget guard for DeepSeek Harness: strips redundant syntax, prunes noisy log lines, and enforces a token ceiling so the context window never overflows.

Three independent language channels for model output — tool-call descriptions (every tool-call card title, including run_code in PTC-style presets), thinking, and replies — each set to follow the web GUI language, force a specific language, or turn off (default: only descriptions, following the GUI). One global runtime-context prompt directive on the host; the client half reports the GUI language; a Settings plugin card switches the modes.

Forces periodic Engram memory recall and save reminders for DeepSeek Harness agents: injects a dynamic system-prompt context that reminds the model to load prior session memory at the start of a session, and to save new decisions/bugfixes/learnings every

Single-password authentication gate for the dsh web surface: configurable session validity, Ctrl+Shift+L lock, CLI password management, brute-force lockout, in-UI password controls.

Branch-role guard for AI coding agents: configurable integration/preview/production/archive roles, blocking direct push, force-push and delete on protected branches and agent merges into production/archive.

Dual-model auto-routing plugin: low-cost direct / high-cost upgrade with an escape-learning closed loop (wrong direct answers auto-learn fingerprints, force-upgrading the same fingerprint next time), persisted and interoperable with the Python ModelRouter.

Safe, audited SQLite/PostgreSQL/MySQL access for dsh agents: schema introspection, enforced read-only queries, a write approval gate, and a durable JSONL SQL audit trail.

Enforce configurable git commit / push / PR conventions for DeepSeek Harness agents

DSH sidebar footer ordering: forces the sidebar.footer.action slot into a vertical stack and lets users configure the top-to-bottom order of its entries.