Stock Pattern Screener

使用7种技术形态检测器（杯柄、三周紧绑、高紧旗、VCP、NR7等）按确定性顺序扫描股票池，支持跨检测器评分校准与置信度聚合排序。

This skill appears to be a genuine stock-pattern screening/backtest blueprint, but there are important mismatches and runtime behaviors to consider before installing or running it: - Expect runtime dependency installation: SKILL.md and references require Python 3.12+, the 'uv' manager, and the zvt package. Although the registry shows no required env or install steps, the skill's preconditions instruct the agent to run pip install zvt and initialize ~/.zvt. Treat those runtime installs as network activity and potential code execution. - File-system writes: The skill will check and may create/modify a ZVT_HOME directory (~/.zvt) and relies on host workspace paths referenced in seed.yaml. If you allow it to run, do so in a sandbox or VM if you don't want it touching your real home/workspace. - No upfront credential disclosure: The skill prompts for data providers (eastmoney, joinquant, akshare, qmt). Some providers require API keys/accounts (joinquant, brokers). Do not supply API keys or secrets until you verify precisely where/how they will be used; prefer ephemeral or read-only test credentials. - Ask for clarification / request explicit install manifest: Request the author supply a clear install spec (exact pip/uv packages and trusted sources) and a list of environment variables/credentials the skill will ever ask for. If you cannot verify, run the skill only in an isolated environment. - Audit seed.yaml and references: The skill's seed.yaml contains runtime rules (must re-read seed.yaml before decisions) and execution protocols. Review references/seed.yaml and references/LOCKS.md to ensure the 'semantic locks' and preconditions align with your expected workflow. If you plan to proceed: run the skill in a disposable environment (container/VM) first, deny network access if you want to inspect behavior offline, and do not provide production credentials or access to real trading accounts until you have full visibility into what it executes.

Type: OpenClaw Skill Name: stock-pattern-screener Version: 0.3.3 The skill bundle is a highly structured blueprint for a financial quantitative analysis agent focused on stock pattern screening and backtesting. It defines a complex 'Setup Engine' with 7 technical indicators (VCP, Cup-and-Handle, etc.) and includes extensive 'Semantic Locks' (SL-01 to SL-12) and constraints (finance-C-*) to prevent common trading errors like look-ahead bias and improper order sequencing. While it includes capabilities for server authentication (KUC-005) and social media data collection (KUC-002), these are contextually aligned with the stated purpose of a market copilot. The bundle even includes security-positive constraints, such as finance-C-256, which explicitly forbids the automatic capture of sensitive credentials in debug artifacts. No evidence of malicious intent, data exfiltration, or harmful prompt injection was found.