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계량경제학 연구 보조 도구: 방법 선택, 데이터 준비, 모형 명세, Python/R/Stata 코드 템플릿을 활용한 실증 분석, 강건성 검정, 결과 보고를 다루는 6개 도구를 제공합니다.

DSH용 remove-pdf-background-gray 스킬 등록: 이미지 기반 PDF의 회색/오프화이트 스캔 배경을 흰색으로 바꾸면서 해상도, 페이지 형상 및 앤티앨리어싱된 텍스트 가장자리를 보존하고(무손실 Flate 재기록), 단일 Python 스크립트(pypdf + Pillow + numpy)로 처리.

harmonyos-dev-mcp Python MCP 서버를 DSH에 연결: 디바이스 검색, 빌드/설치/실행/제거, UI 자동화(클릭/입력/키/스와이프/스크린샷), E2E UI 트리 검사, 로그/크래시 분석을 18개의 mcp__harmonyos__* 도구로 제공합니다.

PR 평가 및 개선 컨설턴트: 과거의 안티패턴과 성공 패턴을 바탕으로 PR 성공 확률을 평가하고, 원클릭 점수 산정 및 실행 가능한 제안을 제공합니다.

Unreal Engine .uasset을 검사(resolve/registry/load)하고, 내장 UE Python으로 제한된 Blueprint 노드 편집을 수행합니다.

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.

컴포저용 중국 대응 음성 입력입니다. 로컬 Python 브리지가 필요합니다 (pip install dashscope websockets, bridge/voice-bridge.py 실행) — 플러그인만으로는 작동하지 않습니다. 브라우저 마이크가 16kHz PCM을 브리지로 스트리밍하고, Alibaba Cloud DashScope ASR(paraformer-realtime-v2)를 실행합니다. 중간 결과가 커서 위치의 초안을 채우며, 무음 시 자동 정지, 선택적 자동 전송을 지원합니다.

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.