SSQ Prediction

AI Investment Research - Double Color Ball (双色球) Prediction. Fetches historical data, applies Contextual Quantum-like Bayesian Network (CQ-BN) model, and sen...

Security Scan

The skill's requirements and runtime instructions are internally consistent with its stated purpose (lottery prediction and optional Feishu delivery); it is instruction-only, requests no secrets, and uses the OpenClaw Feishu integration as described.

Purpose & Capability

Name/description (SSQ prediction) align with what the skill asks for: fetching public SSQ history, running a model (described in prose), and optionally sending results to Feishu via the openclaw CLI. The only external requirement is the openclaw binary for message delivery, which matches the delivery capability.

Instruction Scope

SKILL.md instructs the agent to fetch historical data from a public endpoint (datachart.500.com), run an internal CQ-BN simulation described in prompt form, format a report, and optionally call openclaw to send a Feishu message. The instructions do not ask the agent to read unrelated local files, harvest environment secrets, or post data to unexpected external endpoints. The model/computation is described as an LLM role-play (quantum physicist) rather than invoking external code; this is consistent with an instruction-only skill.

Install Mechanism

No install spec or downloadable code is present (instruction-only). This minimizes installation risk — nothing is written to disk by the skill itself.

Credentials

No credentials or sensitive environment variables are required. The SKILL.md documents a single optional variable (FEISHU_SSQ_GROUP_ID) used only to select the Feishu target; that is proportional to the delivery feature. No unrelated secrets or config paths are requested.

Persistence & Privilege

always is false and the skill does not request persistent system-wide privileges or modify other skills. It relies on platform-level Feishu auth handled by OpenClaw and will only send messages when run (or if the optional FEISHU_SSQ_GROUP_ID is set).

Assessment

This skill is coherent: it fetches public historical lottery data, asks the agent (LLM) to simulate a model, and optionally posts the formatted report to a Feishu group via the openclaw CLI. Before installing, confirm: (1) the OpenClaw platform already has Feishu configured and you are comfortable with the skill posting to the specified group (only set FEISHU_SSQ_GROUP_ID if you want automatic posting), (2) your environment allows outbound HTTP requests to the datachart.500.com endpoint, and (3) you understand the prediction is speculative — the SKILL.md is a prompt-driven model description rather than audited code, so there is no guarantee of scientific validity. Because the skill is instruction-only and asks for no secrets, the security risk is low; if you need stronger assurance, request the author provide an auditable implementation or explicit details of the numerical algorithm used.

Double Color Ball Prediction (SSQ)

This skill automates the prediction of Double Color Ball (双色球) lottery numbers using a "Contextual Quantum-like Bayesian Network" (CQ-BN) model simulation.

Dependencies

• openclaw CLI: Required for Feishu message delivery. This is provided by the OpenClaw platform itself.
• Feishu authentication: This skill uses OpenClaw's existing Feishu integration (already configured at the platform level). No additional credentials or tokens are required.
• FEISHU_SSQ_GROUP_ID (optional): Set this environment variable to your target Feishu group ID to enable automatic delivery. If not set, the report is output directly in the current chat session.

Configuration

Variable	Required	Description
FEISHU_SSQ_GROUP_ID	No	Feishu group ID for report delivery

Workflow

1. Data Acquisition

   • Fetch recent 200 periods of SSQ historical data from:

     https://datachart.500.com/ssq/history/newinc/history.php?start=24001&end=24200
     

   • Adjust start and end parameters dynamically to retrieve the most recent 200 periods.

2. Model Execution (CQ-BN Simulation)

   • Context: You are a quantum physicist building a mathematical model.
   • Logic:
     • Interference Term: Calculate "constructive interference" zones between red balls.
     • Hilbert Space Mapping: Map red balls (1–33) to a Hilbert space; identify high-energy "potential wells".
     • Phase Collapse: Predict the "collapse point" of probability waves for the next draw.
   • Refinement:
     • Generate an initial Top 20 combinations.
     • Analyze frequency of numbers in the Top 20 to find the "resonance" set (most frequent numbers).
     • Re-combine high-frequency numbers to form a final Top 10.

3. Output Formatting

   Generate a report with the following structure:

   【 🔔AI投资研究院-双色球预测 [YYYY-MM-DD]】
   
   ### 【上下文相关量子贝叶斯网络模型 (Contextual Quantum-like Bayesian Network, CQ-BN)】
   
   **模型运行报告：**
   - 数据已映射至 Hilbert 空间
   - 在 [区间] 检测到量子干涉
   - 概率波坍缩点预测完成
   
   **Top 10 推荐组合：**
   1. 红球：[R1]、[R2]、[R3]、[R4]、[R5]、[R6]，蓝球：[B1]
   2. ...
   
   ⚠️ 风险提示：量子概率坍缩具有随机性，模型结果仅供数学研究参考，不构成绝对投资建议。请理性购彩。
   

4. Delivery

   • If FEISHU_SSQ_GROUP_ID is set, send the report to that Feishu group via OpenClaw's built-in Feishu integration:

     openclaw message send --channel feishu --target "$FEISHU_SSQ_GROUP_ID" --message "<report>"
     

   • Authentication is handled by OpenClaw's platform-level Feishu configuration — no extra tokens needed.
   • If FEISHU_SSQ_GROUP_ID is not set, output the report directly in the current chat session.