Plugins

Local-first resume warehouse for DeepSeek Harness: package your work into reusable bullets, import an existing resume into a template, analyse a job description (including the school-tier preference it implies), assemble a tailored Chinese or English resume and export a PDF named position-name-school. The whole app ships inside the npm package — server/, web/, skills/, scripts/, requirements.txt, no git clone needed — and one tool starts, stops and health-checks it; the first start installs the dependencies into app/.venv. Needs Python 3.10+ and macOS or Linux (bash). Nothing leaves the machine except the LLM calls you confirm.

Requirement-to-evidence audit for DSH sessions: maps each requirement to tool calls, files and commands, records per-requirement verification, and sends missing items back to the agent.

Measures one university department's research output: matches author affiliation strings against a college's known name variants (detecting same-named departments at other universities), backfills papers that only name the university by faculty author IDs, classifies each paper by journal tier (CAS partition with Top flag, JCR quartile, CCF, Chinese core via a CNKI export merger), splits staff from student first authors, and writes a workbook with a dashboard sheet, a filterable paper list, a teacher-by-direction matrix and per-teacher statistics. Student authorship is inferred from affiliation and staff lists, not verified against enrolment records. Requires Python 3.9+ with pandas and openpyxl (pip install -r requirements.txt); papers come from the OpenAlex API, whose free per-IP quota is limited, and Chinese-journal coverage needs a manual CNKI export.

Gitee Enterprise work-item workbench in the Harness sidebar: browse projects and tasks, requirements, and bugs; inspect details, child tasks, comments, and Markdown; create or edit work items; and reference them with @.

DSH-elysia — shared Markdown memory for every DSH session: persona, requirements, corrections, lessons, methods, requests, sessions, a method library and ingested documents, mirrored to a second disk with version snapshots and a cross-process write lock; entries move between the main file and a searchable archive by hit frequency and repeated emphasis, and retrieval is keyword co-occurrence plus BM25. Ships a skills library (SKILL.md playbooks with optional guarded run.mjs execution), a sticker library that sends a fitting sticker at the right moment, and — new in 1.10 — Memory Packs: a bundled, opt-in character memory (packs/elysia: 61,903-char identity + 2,482-char persona distilled from 1,696 official voice lines and 112,175 dialogue lines). Packs are off by default, back up before writing, only touch identity/persona, and can be uninstalled to restore what was there.

End-to-end PowerPoint assistant preset for DeepSeek Harness with editable deck generation, template-preserving edits, rendering and structural quality checks. Needs Python 3.10+ with requirements.txt installed; rendering also needs LibreOffice and pdftoppm, and OCR of scanned documents needs Tesseract.

Beta: a project supervisor for DeepSeek Harness — standing rules plus a Web panel (three switches, dispatch modes) that splits a goal into parallel teammate dialogs, checks engineering baselines, interviews new-project requirements and protects beginners. The standing rules come from the repo kit installer, an optional separate step.

Extracts deadlines, deposit, validity, ceiling, bid composition and copy counts from a tender document, and reports the items it did not find rather than omitting them.

Project Development Mode preset plus an in-chat development board for DeepSeek Harness: the lead conversation clarifies requirements and delegates to an Agent Team, and the floating board tracks each user change request through dispatch, execution, testing and acceptance with 7 board tools.

Skill-creation console for the Web UI: fetches the official creator skills, hands the requirements to the Huawei Cloud, generic, or REST API creator, then scores the generated skill against a 10-point rubric and returns the itemised deductions to the creator until it reaches 8.5/10.

Evidence-first reuse skill for DeepSeek Harness: before implementing, porting, choosing dependencies, or troubleshooting a tool, it searches the local project and machine for existing solutions in layers, judges reuse on checkable evidence, refuses reuse when essential requirements or risks are unmet, and reports what could not be verified. Ships as a DSH bundle that registers the skill on ctx.skills.

OCR for scanned, image-only PDFs into Markdown, built around the fact that a book takes about an hour: every page is checkpointed so an interrupted run resumes, a progress log reports live status, and a quality report names empty pages and low-confidence lines. Requires Python 3.10+ and pip install -r requirements; the first run downloads the OCR model.

Registers two tools for DeepSeek Harness. `doc_ocr` turns scanned PDFs and images into structured text (per-page text, financial tables with a balance-sheet tie-out check, contract-clause hits) through a local RapidOCR engine or a Zhipu GLM-OCR cloud engine, and `doc_preprocess` turns a directory of raw files into an Obsidian-ready knowledge base through a seven-stage pipeline with backend routing and sha256-based incremental skipping. Numbers that fail the tie-out are reported, not invented. The local engine needs Python 3 with rapidocr-onnxruntime, pypdfium2 and Pillow (pip install -r requirements.txt); the GLM engine needs ZHIPU_API_KEY.

Skill-creation console for the Web UI: fetches the official creator skills, hands the requirements to the Huawei Cloud, generic, or REST API creator, then scores the generated skill against a 10-point rubric and returns the itemised deductions to the creator until it reaches 8.5/10.

A DSH plugin that automates shipping a local project: create a GitHub repository and publish it (git init/commit/push + topics + tag + release), sync requirements/progress to Linear, publish to npm, and announce in the community Discussions — to join the

An agent preset that turns a one-line idea into requirements, tech plan and maintenance baseline — every step is restated and confirmed by you before proceeding. No scenario presets: 73 atomic skills (6 master skills + a verify dispatcher + 66 sub-skills) load by context.