Bull Stock King: Institutional & Hot Money Resonance Stock Selection – Consolidating Institutional Capital and Hot Money Trends into a Single Screening List
Bull Stock King - Institutional and Hot Money Resonance Stock Screener is an A-share stock screening Skill published on SkillHub (community source, version 1.0.0, category: professional). It first screens stocks using institutional capital, then screens based on hot money movements, takes the intersection of the two, and identifies individual stocks that attract attention from both types of funds. It provides three premium strategies: Mainline Leader Capture (for short-term hotspots), Swing Hidden Entry (for mid-term swing trading), and Small-Cap High-Quality Growth (for growth dark horses). The documentation states requires_api_key=false. The article introduces the dual screening logic, three strategies, verifiable deployment information, typical usage, applicable limitations, and truthfully states that the documentation does not provide installation commands, invocation examples, or internal parameters of the strategies.
Read Moredsh-auth-cookie-guard：Reserving Request Header Budget for Local Listeners and Retiring Old Startup Cookies
Introducing the DSH Community Host plugin **dsh-auth-cookie-guard** (jitianjiyan). Repeated launches with a fixed profile lead to the accumulation of `dsh-auth` startup cookies on 127.0.0.1, causing the Cookie header to exceed Node’s default 16 KiB limit and resulting in 431 errors. This manifests as an unrecoverable failure in desktop welcome authentication. The plugin increases `maxHeaderSize` (default 64 KiB) after the web server is ready, preserves a specified number of cookies (`keep`) and those for the current port in request order, and removes the rest in batches. Install via `dsh plugin add dsh-auth-cookie-guard`, with optional `maxHeaderBytes` and `keep` configurations. Includes notes on security boundaries and multiple instances on the same host.
Read MoreExam Paper Layout: A3 Two-Column Paper, Sealing Line, Auto-Statistics of Question Numbers and Scores, Answer Sheet Separation: Format Word Drafts into Formal Exam Papers Locally
Introducing the community Skill "Exam Paper Layout - A3 Two-Column - Sealed Line - Auto-Statistics - Answer Sheet Separation" (@user_9b6e0382/satloot-exam-paper, v0.1.0, community, category: education, rating: 100000, downloads: 1521). It accepts drafts written in a specific format (main section titles with total scores, numbered sub-questions, options A/B/C/D, and [Answer] markers) and formats them into A4 single-column or A3 landscape two-column layouts with a seal line on the left and writing fields on the front page. It automatically generates headers, exam time/full marks, question number/score tables, and page numbers. It renumbers questions, verifies score sums (alerting if totals mismatch), calculates points for blanks, and arranges multiple-choice options efficiently. Graphics, formulas, and tables are preserved (auto-scaling if too wide), while solution-based questions get blank space. It outputs a separate answer sheet and a question statistics table. Results are saved as new files without altering originals. It works offline (requesting permission to install python-docx if missing) and supports converting to PDF via Word or WPS. It does not contain built-in exam questions or formats mimicking standardized tests like the Zhongkao or Gaokao.
Read MoreOctopus | User Scenarios and Task Analysis: Turning Comments and Discussions into a Task List
**Introduction to the community-published Skill "Octopus | User Usage Scenario and Task Analysis"**, maintained by user_2d9d1ec9, version 1.0.0, categorized under data-analysis. It requires no API Key and is a top-level Skill manually triggered by customers. It takes Amazon Product Reviews, Octopus public discussions, and users' existing data as inputs, decomposes them along four dimensions—scenarios, goals, obstacles, and expected results—and outputs three categories of task lists: functional tasks, emotional tasks, and social tasks. It is suitable for JTBD (Jobs to be Done) user task analysis. This article describes its positioning, verified core capabilities, official entry point, typical usage, and limitations. The official installation command and configuration fields could not be verified at the time of scraping and were not fabricated.
Read MoreAgentCompare (dsh-agent-compare): Real execution of two versions for the same requirement; adopt after testing and review.
AgentCompare is a DSH community workflow plugin (MIT licensed, preview version 0.2.0-alpha.18) that generates two Vite frontend implementations in parallel for the same requirement, builds each one, and provides A/B preview in the conversation. It supports "two strategies with the same model" or "two models with the same requirement," binds them to unified acceptance criteria for blind selection, and after the reveal, reviews and writes back to the repository. This article, based on the official README, covers installation commands, interface operations, and applicable scope.
Read Moredsh-voice-mode: Full-duplex voice input and sentence-by-sentence playback within DSH sessions
dsh-voice-mode is a DSH client plugin maintained by qishuilalala that provides streaming local speech recognition into drafts during conversations, sentence-by-sentence reading with real-time subtitles, voice interruption, and optional wake words. ASR inference runs on the host side without requiring an additional API key, while TTS defaults to Edge cloud with optional VITS/Kokoro backends. Based on the official README, this article describes the installation command dsh plugin --profile web add dsh-voice-mode, typical operation gestures, settings entry points, and common configuration keys, while noting plugin permissions, online reading behavior, and compatibility boundaries.
Read MoreFacade Detailed Design Drawing Review and Connection Optimization Expert: Systematizing Drawing Review and Connection Optimization into a Reusable Process
This article introduces the SkillHub community skill "Curtain Wall Detailed Design Review and Connection/Node Optimization Assistant - 鹏哥撩工程 Ai" (v1.0.0, professional category, requires_api_key=false). Targeted at curtain wall designers, detailers, contractors, construction supervisors, and owner-side engineering managers, it consolidates eight capabilities into a fixed workflow: construction drawing review, curtain wall system analysis, connection/node detailing optimization, waterproofing and drainage analysis, embedded parts and connection system inspection, interface coordination with the main structure, construction quality control, and leakage troubleshooting. The article provides the official enablement entry point, recommended input fields, three types of reproducible examples (corner node optimization, post-rain leakage investigation, and as-built acceptance checklist), four output skeletons (drawing review comments, connection optimization plan, quality checklist, and leakage risk analysis report), as well as four guiding principles—node priority, waterproofing priority, constructability, and closed-loop management—and handling guidelines for issues such as sealant joint cracking, water leakage, and embedded part misalignment. It also clarifies the boundaries of the skill, stating that it does not replace structural calculations, professional testing, construction method approvals, or supervisory acceptance.
Read Moredsh-purge: Local Compatibility Layer for DeepSeek Harness Desktop
dsh-purge is a DSH client plugin (v1.3.6, MIT) maintained by 555bbbAAA based on upstream 1.1.71. Targeting the Windows desktop host (version 0.2.1-rc.3 segment), it provides patch-to-package swapping, runtime self-healing, tri-state updates, and CLI status queries. Based on README and INSTALL.md, this article describes the compatibility scope, core capabilities, PowerShell installation and registration steps, verification methods (--status / --swap-asar / --uninstall), as well as local file modification permissions and known limitations.
Read MoreOverseas Litigation Case Database: Cross-Jurisdictional Precedent Search and Compliance Insights
Overseas Litigation Case Database (@user_44ebfc99/cue-overseas-litigation, v1.0.5, community/professional) is a retrieval-based Agent Skill. It centers on a specific topic to retrieve public precedents and regulatory announcements from major legal jurisdictions, summarizes the structure of causes of action, judicial tendencies, and actionable compliance insights for Chinese entities. Core requirements mandate that key assertions include original citations or links, and that no precedents, case numbers, penalty amounts, or legal provisions be fabricated. In cases of insufficient sources, the system must state this explicitly and substitute with verifiable official documents. For non-English jurisdictions, original terminology is preserved with supplementary Chinese explanations. Materials are organized into three layers: scripts/ provides scripts for case database retrieval, judgment extraction, and trend aggregation, while references/ offers manuals on legal jurisdictions, court official websites, and citation formats. Running the skill requires an API key and supports three installation methods: Cursor, Codex CLI, and Claude Code. It is suitable for preliminary research on cross-border compliance regarding sanctions and export controls, but does not constitute legal advice.
Read MoreIntelligent Essay Grading: Delegating Composition Correction and Writing Assessment to Skill
Essay intelligent grading and scoring is an education-focused large model skill launched by Kunlun Growth. It is located at @kunlungrowth/edu-essay-grader, version 1.2.1. It targets Chinese and English essays, and outputs scores, essay comments, and upgrade suggestions according to scoring criteria, covering grading of Chinese and English compositions in middle school and college entrance exams as well as daily teaching feedback. Trigger words include essay grading, Chinese composition, English essay, scoring criteria, writing evaluation, essay comments, and correction. The article explains its functional boundaries, triggering methods, precautions for activation, and the limitation of requiring verification of rubric suitability before grading formal exams.
Read MoreOne-Click Generation of Hand-drawn Comic Story Videos: From Story Text to 16:9 Finished Animation
This community Skill (@indiv-dfteacher/fmg-autoshouhui-vidio, v1.0.2, design-media) automatically converts Chinese story text or ordered images into finished 16:9 videos featuring a hand-drawn comic style. It first utilizes *story-to-handdrawn-video* to generate and render colored pencil diary-style storyboard illustrations, then invokes *fmg-autojy-video* to synthesize the final product with AI voiceovers, cover pages, background music (with auto-ducking to ensure voices remain clear), and subtitles. First-time usage guides the user through downloading local dependencies and deployment self-checks. The tag indicates requires_api_key=false. The article outlines what the tool is, its core features, how to enable it via coordinates, the official typical workflow, applicable scenarios, and precautions. Installation commands and specific parameters were not listed in the official documentation and have therefore not been fabricated.
Read Moredsh-soul: Independent Memory, Graph Compression, and Controlled Harness Evolution
DSH-soul 2.0.0 is a DSH workflow plugin maintained by icyaaaww. By default, it enables a memory skeleton (graph nodes, 600-byte projections, and soul_recall) and offers an optional graph compression backend to replace model summaries. Evolution is disabled by default; when explicitly enabled, it compiles experience into C1–C8 modifications, validated through pairwise verification, shadow trials, and checks acceptance. It requires Node.js 24+ and DSH ≥0.2.1-rc.2. Installation is performed using the `dsh plugin --profile` command pointing to a local tgz file. It is ideal for scenarios requiring long-session constraint retention, reduced compression costs, and controlled iterative harnesses.
Read MoreModeling Lottery Rules and Cross-Lottery Analysis: Upgrading Single-Lottery Experience to Cross-Lottery Consistency Verification
# Introduction Practitioners of lottery data analysis frequently encounter two categories of problems. The first is directly applying patterns from the "Double Color Ball" to the "Super Lotto," only to find that the patterns fail after switching lottery types. The second involves uncovering a multitude of "patterns" within a single lottery type, yet failing to distinguish between genuine structural patterns and small-sample noise. The common root cause of these issues is the lack of cross-lottery comparison: any pattern within a single lottery can be explained away as "lottery-specific noise." Only by testing these patterns for reproducibility across multiple lottery types can one determine their transferability. The Skill introduced below turns this process into a reusable analytical workflow. ## What is this "Lottery Rule Modeling and Cross-Lottery Analysis" is an Agent Skill designed for the analysis of lottery rules and probability structures. It is maintained by the community publisher user_04b42a16 and located at @user_.
Read MoreDrawing Review and Design Optimization Consultant – Brother Peng's Engineering AI: A Pocket Guide to Review Essentials and Value-Creation Cases
This Skill packages the accumulated drawing review checklists from regional subsidiaries of central state-owned enterprises (SOEs) and 237 optimization cases into a knowledge base of approximately 8,300 words. It covers review criteria and procedures, key points for nine professional disciplines, twelve categories of high-frequency optimization techniques, six major directions for value creation, and a risk boundary database. By simply inputting the project phase and discipline, users can generate drawing review logs, discipline-specific review checklists, optimization proposals, value-creation planning outlines, risk alert lists, and case study cards. It requires no data uploads or API keys. Please note: This tool does not replace design validation or official documentation. Optimization outputs involving mandatory codes, structural safety, fire protection, and specialized acceptance serve only as reference leads. Value-creation figures are derived from specific cases in the source data and must be recalculated for new projects.
Read Moredsh-media-desk: Complete Inspiration, Drafting, and Scheduling in the DSH Sidebar
dsh-media-desk is a community workflow plugin for DeepSeek Harness. It provides an inspiration wall in the sidebar, one-click generation of voiceover scripts, covers, illustrations, and storyboards, as well as content management, calendar scheduling, data review, and style presets. Data is stored in ~/.dsh/media-desk/. It requires DSH 0.2.x version 0.2.1-rc.5 or above. Download the tgz from Releases and install it using `dsh plugin add file:`. Text models use DSH configuration, while image generation and optional Monid account scraping require your own API keys. Open source under the MIT license, it cannot post content to platforms on your behalf.
Read Moredsh-marktext: Edit Markdown in DSH Right Sidebar Using MarkText Style
dsh-marktext, maintained by Roland0511, embeds @muyajs/core into the DeepSeek Harness sidebar, supporting WYSIWYG editing for *.md files, offline extensions like KaTeX/Mermaid, auto-save, and version guard write-back. Based on the official README, this article covers installation (in-app dsh-marktext, web profile CLI, and manual desktop package.json), the iframe architecture, diagnostic interfaces, and notes regarding mutual exclusivity with dsh-markdown-typora. Requires DSH 0.2.1+. MIT License.
Read MoreAI Large Model Expert | AI Image and Video Marketing for Renovation Companies: Introduction to AI Content Marketing Skills for Home Improvement Businesses
Introducing **@infimind/industry-renovation-company-marketing-ai-hive** (Version 1.0.0, Category: Design & Media) on SkillHub. Targeting homebuyers, tenants, homeowners, renovation clients, community residents, and project decision-makers, this tool centers on real-life cases, materials, craftsmanship, budgets, and construction progress. It generates audience and selling point strategies, 30-day content calendars, image asset matrices, short video columns and storyboards, itemized prompts, cross-platform adaptations, AI-HIVE task logs, and review metrics. Additionally, it facilitates AI-HIVE interactions by allowing queries for current image/video models, uploading reference materials with usage rights, saving price snapshots, routing based on cost/speed/success rate, polling for downloads, and logging taskIds. It is suitable for Douyin, Xiaohongshu, WeChat Channels, real estate and home furnishing platforms, WeChat Official Accounts, and private domain traffic. **Authenticity Boundaries:** Distinctions must be made between real-life footage and schematic illustrations regarding property listings, area, location, price, materials, construction duration, and effects; fabrication of projects is prohibited. No guarantees are made regarding viral success, sales volume, rankings, audit approval, or return on investment. **Tag:** `requires_api_key=true`
Read Moredsh-familiar-memory (dsh-neuron-memory): DSH Local Memory Layer
Elio896's dsh-familiar-memory (package name dsh-neuron-memory v0.2.0) provides local SQLite memory for DeepSeek Harness, featuring FTS5 literal recall, sentiment buckets with same-day context, exponential decay, and bottom-out archiving; vector and graph features are disabled by default. It achieves session continuity via neuron_opening/neuron_handoff, while the "work" scope uses supersedes to mark the latest decisions. Installation requires executing node install.mjs in the plugin directory and dsh plugin add link:<directory>, with configuration options for db, halfLifeDays, autoSync, etc. Data is not uploaded; automatic logging reads ~/.dsh/sessions/, so source code and permissions should be reviewed independently. MIT licensed third-party plugin.
Read MoreDesktop Pet: Replace the Pet Image with a GIF
"Desktop Pet" is a community Skill, located at @user_8fd82e77/zmcw-20260819, version 1.0.0, category dev-programming, publisher user_8fd82e77, with the brief description "Generate a desktop pet that can upload GIF images to replace related actions." It is positioned as a tool for changing a desktop pet’s appearance, using a v8 single-window composition architecture: it takes the user-submitted one idle-display GIF and several randomly played GIFs, removes the background onto a white base, generates project assets under E:\desktop-pet, registers the result as a "random playback every 5 seconds" effect, and repackages it into a desktop pet exe, so as to replace “布丁店长” with any anime/cartoon character design. It includes a self-contained background-removal script references/gen_swap.py, supporting two modes: light neutral-white and dark floodFill. A SkillHub page snapshot shows a rating of 100000, 1321 downloads, and 0 installations, with the tag requires_api_key=false. Installation follows the generic SKILL.md format by adding the Skill URL; there is no verified package-manager command. It is aimed at users who want to replace the appearance without manually modifying the project, and also works for collaborators to use independently.
Read MoreLet it be | Accuracy Check: A Structured Toolkit Skill for Traditional Numerology
"Forget It | Is It Accurate?" is a life-service Skill on SkillHub created by Cunlao Xie. It provides people who want to experiment with traditional divinatory arts with a computable, table-driven, framework-based toolkit composed of ten modules, covering Bazi (Four Pillars of Destiny) chart casting, Zi Wei Dou Shu, Qi Men Dun Jia, I Ching hexagram interpretation, Chinese zodiac fortune, Eight Mansions feng shui, name creation and name matching, tarot, personality-color analysis, and numerology. It addresses two specific problems: first, unified standards—built-in authoritative tables and algorithms lock in the casting rules and terminology for the ten systems to prevent inconsistent chart outputs from one generation to another; second, clear boundaries—it only presents structured results and does not output specific good/bad fortune predictions, and its results include a disclaimer that it is intended only for entertainment and traditional cultural research. The article introduces the positioning, a capability list for the ten modules, reproducible usage examples reconstructed from trigger words, as well as applicable scenarios, limitations, and pitfalls, including that it does not provide fortune predictions, that the built-in standards should be taken as authoritative, and that official documentation should be checked before integration.
Read MoreDesigning an Exercise Plan for Weight Loss: Transforming Fat Loss Goals into Actionable Exercise Prescriptions
"Creating an Exercise-Based Weight Loss Plan" is a community Skill on SkillHub, identified as @user_a549da14/jk-001 (Version 1.0.0, Category: life-service), published by user_a549da14. Centered on exercise prescriptions and supported by essential dietary calorie control principles, it addresses user needs such as weight loss through exercise, developing fat-loss training plans, calculating daily caloric deficits, selecting aerobic/strength combinations, and breaking through plateaus. It requires no API Key and is based on the general SKILL.md format. As the official page does not provide installation commands or configuration fields, the activation method depends on the Agent client's requirements for the Skill directory. It is suitable for handling targeted fat-loss inquiries within conversational products; however, the dietary section only covers principles of calorie control and does not replace professional nutritional or medical advice.
Read Moredsh-prompt-rewriter: One-click Rewrite of Drafts into Actionable Prompts Next to the Input Box
dsh-prompt-rewriter is a DeepSeek Harness community plugin maintained by huaguoxingkong. It provides a whale tail button next to the session input box that uses the current or a specified model to rewrite short drafts in-place into executable prompts containing objectives, formats, and boundaries. It only replaces the input box content without automatically sending it and supports Ctrl+Z and rollback. The introduction covers installation commands (npm / GitHub / Release), settings, context and image boundaries, shortcuts, and precautions, facilitating reduced multi-turn trial and error in model inference scenarios.
Read MoreAurabot (dsh-aurabot-qq): Integrating DSH AI as the QQ Bot "大肥鱼" for Chat
Aurabot (dsh-aurabot-qq) is a DeepSeek Harness client plugin that connects to the QQ alt account "大肥鱼" via SnowLuma or OneBot v11. It provides a full-page dashboard, with the master switch disabled and dry-run enabled by default, and offers modular capabilities covering private and group chats, personality/memory/mood systems, voice and emoji, Qzone, Bilibili, Douyin, Hexbox, and cover songs, with support for custom modules via a configurable data directory. Based on the official README, this article describes the architecture, installation commands, wizard steps, and Linux limitations, and provides typical usage examples and permission considerations.
Read MoreSelf-Improving + Proactive Agent (Pro Edition): Empowering Agents to Review, Self-Correct, and Accumulate Experience
Self-Improving + Proactive Agent (Pro Edition) is a community skill on SkillHub, located at @user_87f6522b/self-improving-proactive-agent, version 1.0.0, category ai-agent. It wires self-assessment, self-criticism, self-learning, and self-organizing memory into a fixed workflow that requires a one-sentence conclusion up front, delivery of a structured result file, and clear annotation of the evidence behind key decisions. Triggers include directly mentioning the skill name, asking how to do something, or asking the agent for help; there are five task scenarios: operation failure, user correction, outdated knowledge, discovery of a better approach, and explicit user installation or reference. The article outlines core capabilities, installation and activation methods, five reproducible typical use cases, as well as applicable scenarios and limitations. While writing, the official URL could not be opened; please refer to SkillHub for the installation command and page data.
Read MoreMoney-Finding Radar | Discover How You Can Make Money: Scan Your Personal Monetizable Assets into a List
**Money-Picking Radar** (@indiv-cunzhanglaoxie/asset-radar) is a community Skill categorized under business-ops, version 1.1.12, requires_api_key=false, created by Village Elder Lao Xie. It systematically scans your personal monetizable assets, using the four fundamental laws of logic (Law of Exchange / Law of Asymmetry / Law of Stock / Law of Minimum Closed Loop) to determine *why* something can be monetized, employs a five-dimensional scan (Skills / Inventory / Network / Time / Information Gap, five questions per dimension) to find out *what* you have, and ranks items using three valuation questions (Monetization Difficulty / Single-Transaction Value / Startup Speed) to output a Top 5 money-picking list, each item accompanied by this week's first step. Red lines: it only produces zero-cost startup plans—no income promises, refuses to scan gray-area information gaps, refuses to exploit acquaintance networks, refuses prerequisites of large upfront investment before monetization; if you want to scale up, switch to the OPC Business Model Designer—the Radar handles *finding*, OPC handles *scaling*. Enable via the official address and trigger with phrases such as "what can I do to make money," "asset inventory," "side hustle," "first dollar," etc.
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