Multi-Agent Stock Research Roundtable System: Enabling 6 Analysts and an Editor-in-Chief to Collaborate on A-Share Research
The Multi-Agent Stock Research Roundtable System is a community-sourced Skill published by user_231765ee, categorized as "professional," versioned at 1.0.0, and located at @user_231765ee/muti-agent-stock. It employs multi-agent simulation to mimic a real investment research team, comprising a roundtable of six professional analysts and one executive research editor. This setup provides multi-perspective cross-verification analysis for A-share investment inquiries and generates structured research reports. This article outlines its positioning, verifiable features (multi-agent roundtable, 6+1 roles, A-shares, multi-perspective cross-verification, structured reports), installation and activation methods, typical usage, as well as applicable scenarios and limitations. It is important to note that since official documentation does not disclose specific analyst roles, report fields, reproducible examples, installation commands, or configuration items, and the tag is marked as `requires_api_key=false`, no speculation is made regarding these details. The page displays a rating of 100,000, 623 downloads, and 0 installations; please refer to official real-time data for accuracy. While suitable for scenarios requiring multi-perspective analysis of A-share issues, as a community-sourced tool, its multi-agent conclusions still require manual review.
Read MoreEnterprise Dishonesty/Risk Information Verification Tool: Structured Corporate Due Diligence Skill Based on Three-Platform Cross-Verification
This skill aggregates company information from three platforms — Qichacha, China Credit, and China Public Credit Information System — and cross-validates it across ten dimensions: industrial and commercial registration, annual report disclosure, historical changes, administrative penalties, administrative licensing, trusted/discredited lists, business abnormalities, serious illegal and dishonest acts, random inspections, and judicial risks. It outputs a structured due diligence report, eliminating the need to manually switch between multiple websites and stitch information together. Location: @user_75a20f40/laozhuang-b03; version 1.0.0; source: community; category: business-ops; tags: requires_api_key=false. Trigger phrases cover company verification, company due diligence, dishonesty queries, company risk, background checks, supplier vetting, partner vetting, and more. It is suitable for supplier onboarding screening, partner background checks, and pre-/post-investment due diligence. Note that the absence of records on a single platform does not mean the company has no issues; for major decisions, always refer to the original pages on the official public system.
Read MoreIn-depth Research: A General-Purpose Research Tool Based on Cross-Validation of Multi-Source Public Data
Cue Deep Research (General Edition) is a general-purpose research Skill released by Beijing Gangyi Intelligent Technology Co., Ltd. It covers public data across A-shares, Hong Kong stocks, US stocks, business registration, judicial records, regulations, supervision, research reports, capital flows, and bidding. The tool supports transforming search results into structured reports with original source links and is capable of replicating the writing style of specified documents.
Read MoreZ律 - Enterprise Information Retrieval: Building a Trusted Enterprise Data Model Using Unified Social Credit Codes
Built upon the Unified Social Credit Code (USCC), Z-Law Enterprise Information Retrieval establishes a four-tier credibility model comprising "Code Access, Data Acquisition, Cross-Verification, and Gold Standard Adjudication." By utilizing six-dimensional, 20-source cross-verification and final adjudication via gsxt, it executes dual-source validation and version tracking on nine core fields. The system outputs structured enterprise due diligence reports with three-color confidence annotations, applicable to scenarios such as business registration information, risk analysis, and judicial risk inquiries.
Read MoreChen Geng – Decision Support: Cross-Validation of Five-Path Models for Personal Decision-Making Skills
The SkillHub community skill "Chengeng-Decision-Crosscheck" (@user_88e00a20/chengeng-decision-crosscheck, v1.1.1) is designed for project direction, collaboration, pacing, and phase reviews. It deconstructs problems into five dimensions for judgment: baseline, current situation, process trends, aptitude, and behavioral patterns. It then performs cross-validation, labels confidence levels, outlines counter-possibilities, and provides actionable recommendations; no API Key is required. The article explains its positioning and boundaries, core capabilities, and the steps for installing the skill from SkillHub into the skills directory of clients such as Cursor, while providing reproducible examples of queries.
Read More