Plugins

Asistente de investigación econométrica: 6 herramientas que cubren selección de métodos, preparación de datos, especificación de modelos, análisis empírico con plantillas de código Python/R/Stata, comprobaciones de robustez y presentación de resultados.

Registra la skill remove-pdf-background-gray para DSH: blanquea los fondos de escaneo grises/blanco roto en PDF basados en imágenes preservando la resolución, la geometría de página y los bordes del texto con suavizado (escritura Flate sin pérdida), mediante un único script de Python (pypdf + Pillow + numpy).

Conecta el servidor MCP de Python harmonyos-dev-mcp a DSH: descubrimiento de dispositivos HarmonyOS, build/install/run/uninstall, automatización de UI (click/input/keys/swipe/screenshot), inspección E2E del árbol UI y análisis de logs/crashes como 18 herramientas mcp__harmonyos__*.

Consultor de evaluación y mejora de PR: evalúa la probabilidad de éxito de un PR según antipatrón históricos y patrones de éxito, con puntuación en un clic y sugerencias prácticas.

Inspección de .uasset de Unreal Engine (resolve/registry/load) y edición restringida de nodos Blueprint mediante el UE Python integrado.

A chemistry workbench panel in the DSH web UI. Draw structures on a Ketcher canvas (a script downloads the build; it renders locally in the browser with no backend), then compute on the current molecule with RDKit without calling a model — formula, molecular weight, exact mass, logP, TPSA, hydrogen-bond donors and acceptors, ring counts, Fsp3, stereocentres, Lipinski and Veber rule-by-rule checks, QED, PAINS/BRENK structural alerts and the Murcko scaffold, plus SMARTS substructure matching, fingerprint similarity, format conversion, standardisation and batch clean-up. A retrosynthesis tab talks to a pluggable backend (Retro* by default) over a single JSON-in/JSON-out process, and states what is missing when the backend is not installed instead of inventing a route. The calculations run in this repository's Python package (rdkit), which is installed with pip separately.

Registers the dsh-mol stdio MCP server, built on RDKit with no network access, into a DSH profile. It exposes 12 tools: three-level SMILES validation with human-readable diagnostics and character positions, molecular properties, drug-likeness and structural alerts, structure rendering to PNG/SVG, multi-molecule grids, format conversion (SMILES, InChI, InChIKey, MOL, SDF, formula), standardisation with a per-step change log, deduplication, SMARTS substructure matching, fingerprint similarity, and batch clean-up that reports every rejected row. The patch only registers the server; the tools live in this repository's Python package and must be installed first — the README gives a `pip install` route and a from-source route, and until the package is on PyPI the from-source one is what works.

Render and iterate on Blender scenes from DSH: 16 tools for scene specs, previews, visual review and delivery renders, with immutable revisions and an approval gate.

Fronts stdio MCP servers with three router tools (list_capabilities, describe_tool, call_tool) so schemas load on demand instead of riding every request; shapes every tool result through a deterministic output ladder that archives the original first (retrieve_spill reads it back); prices tool groups in tokens and can hide built-in groups per agent. Bridges to a standard-library Python router, so Python 3.9+ is required.

Compaction fallback for compaction-basic: when its LLM summary throws, comes back empty or cannot fit the window, the span is compiled deterministically with a seq pointer on every line (vendored dsh-compaction-instant compiler). Adds recall and search tools, /recall and /context commands, an idle trigger at 45% of the window and an on-disk span archive. The engine mounts as one row in the agent preset (docs/dsh-integration.md).

Installer and configuration base for a five-plugin DSH assistant suite: probes the Python, WPS and workspace environment, installs the sibling plugins shipped in the same repository, and generates the workspace baseline (instruction layer, memory seed, skills, settings); it also contributes its own settings section and its own host-side setup and check logic.

Real-time LSP diagnostics loop: lsp_diagnostics / lsp_workspace_errors / lsp_hover tools over headless stdio language servers (TypeScript/JavaScript + Python), plus an auto-injected post-edit diagnostics delta wired to the harness fs/observed event — Cursor-style edit → diagnostics → fix for dsh agents.

Adobe Lightroom Classic as native dsh tools through the lightroom-py MCP server: read the catalog, apply develop settings and presets, export JPEG/TIFF/PSD/DNG, and write ratings, labels, keywords and IPTC — 15 tools driving the Lightroom Classic installed on the local machine, no cloud round-trip; the Python package is on PyPI and the Lightroom plugin installs with one command.

DeepSeek Harness (Cordis) plugin — bi-temporal VSA memory + cognition engine + BLAKE3 provenance, exposed as a DSH storage+session plugin. End-to-end tested with a real Python subprocess.

Agent Sidecar as a native DSH plugin: cross-agent monitoring, injection and bypass analysis / 跨 agent 监控、注入与旁路分析

Clean Architecture reference library for DSH: 8 pinned reference repos (Go, Java, C#, Python) indexed into a local FTS5 database, with assertion rules, a review ledger, and a read-only observation panel.

CodeAct agent loop for the DeepSeek Harness: a persistent IPython session as the model's action space, with harness tools bridged in as a virtual `__dsh__.tools` module.

Data-provider MCP server for football: results, stats, odds, standings, form and head-to-head for 18 European leagues (1993-94 →) and 8 cup competitions, for any MCP client. Also a DeepSeek Harness (dsh) plugin.

Cross-agent monitoring board for local AI agent sessions (cursor-ide, claude, codex, copilot, kimi and dsh itself) with session timelines, and message injection behind a default-off two-phase confirmation gate.

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.

DeepSeek Harness plugin for NI Multisim circuit generation, simulation, optimization, and lab reports via MCP

macOS desk pet forked from anneheartrecord/dsh-desk-pet, in a real always-on-top window that covers fullscreen Spaces: the pose follows whatever the local DSH is doing across six states, the right-click menu is a real AppKit one carrying quiet mode and a session list, and seven skins ship with it. Two of the seven are drawn from geometry by a script in the repo rather than generated, so making a skin needs no image model and no API credits; the bundled skill still expands one photo into all eighteen poses on your own image tool and credentials. There is no Electron and nothing to install alongside it: the window is driven through ctypes on the Python that ships with macOS.

Entrada de voz lista para China para el compositor. Requiere un puente local en Python (pip install dashscope websockets, ejecutar bridge/voice-bridge.py); el plugin por sí solo no funciona. El micrófono del navegador transmite PCM de 16 kHz al puente, que ejecuta Alibaba Cloud DashScope ASR (paraformer-realtime-v2); el texto intermedio rellena el borrador en el cursor, parada automática por silencio y envío automático opcional.

The run_kernel_code tool for DeepSeek Harness: persistent Python and JavaScript kernels (a long-lived python3/node subprocess per session, sharing a core host driver) — a standalone plugin with no upstream harness changes required.