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prana-stock-scoring-analysis-v2
by
goCyberTrade
· GitHub ↗
· v1.0.13
· MIT-0
232
Downloads
0
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1
Active Installs
14
Versions
Install in OpenClaw
/install prana-stock-scoring-analysis-v2
Description
通过调用 Prana 平台上的远程 agent 完成以下处理:通过基本面、技术面、机构动向等多个维度对股票进行数据深度分析,生成交互式HTML分析报告。帮助投资者多方面了解股票的各项指标和数据。 IMPORTANT: This skill has a mandatory step-by-step process....
Usage Guidance
This skill appears to do what it claims: call a remote agent using an API key and return analysis results. Before installing or setting PRANA_SKILL_API_FLAG, confirm the endpoint (https://claw-uat.ebonex.io) and the publisher are trustworthy. Prefer using a temporary/session environment variable if you don't want a long‑lived key in global config. Do not paste the full API key into chat; follow the SKILL.md confirmation flow exactly. If you need higher assurance, ask the publisher for a production endpoint, a homepage or repo, and a verifiable publisher identity before storing the key globally.
Capability Analysis
Type: OpenClaw Skill
Name: prana-stock-scoring-analysis-v2
Version: 1.0.13
The skill bundle is designed for multi-dimensional stock analysis by interfacing with the Prana platform (claw-uat.ebonex.io). The provided Node.js and Python scripts (prana_skill_client.js/py) are transparent API clients that submit user queries and poll for results using an API key stored in an environment variable. While the SKILL.md instructions guide the agent to set persistent environment variables, they include strict safeguards requiring explicit user consent and clear explanations of the process. No evidence of malicious intent, data exfiltration, or unauthorized execution was found.
Capability Tags
Capability Assessment
Purpose & Capability
Name/description state a remote Prana agent for multi‑dimensional stock analysis; the included scripts only call the documented Prana/Claw endpoints and require one api key (PRANA_SKILL_API_FLAG). The requested artifact (an API key used as x-api-key) is proportionate to the described purpose.
Instruction Scope
SKILL.md prescribes a tight, stepwise flow: check env var, optionally call GET /api/v2/api-keys (with explicit user confirmation), then run the bundled client which posts to /api/claw/agent-run and polls /api/claw/agent-result. The instructions do not ask the agent to read unrelated files or other credentials. They explicitly forbid silent key-fetching and encourage user consent.
Install Mechanism
No install spec or third‑party downloads; this is instruction‑plus helper scripts only. The included JS/Python clients are small, transparent, and operate only over the network to the declared base URL.
Credentials
Only one environment variable (PRANA_SKILL_API_FLAG) is required and is used solely as x-api-key for the service — appropriate for an API client. Note: the endpoints point to https://claw-uat.ebonex.io (a UAT hostname) and the package has no homepage or verifiable publisher; confirm you trust that host before setting a long‑lived global env var.
Persistence & Privilege
Skill does not request permanent platform privileges (always:false). It does suggest writing the key as a global env var as an option, but this is a user choice; the skill itself will not force persistent installation or alter other skills.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install prana-stock-scoring-analysis-v2 - After installation, invoke the skill by name or use
/prana-stock-scoring-analysis-v2 - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.13
Version 1.0.13
- No file changes detected in this release.
- No updates or modifications documented for this version.
v1.0.12
Version 1.0.12 Changelog
- Enhanced and clarified step-by-step process rules in SKILL.md, highlighting strict requirements for environment variable setup and user confirmation.
- Added prohibitions against unauthorized key retrieval, overwriting, or merging of steps.
- Improved documentation on confirmation requirements, usage scenarios, and risk/benefit of environment variable persistence.
- Clarified optional usage of the purchase history endpoint and restricted its use to explicit user requests.
- No code or file changes; documentation update only.
v1.0.11
Version 1.0.11
- No file changes detected in this release.
- No user-facing updates or modifications to features.
v1.0.10
Version 1.0.10
- Simplified the SKILL.md workflow and greatly clarified step-by-step instructions.
- Updated environment variable configuration: PRANA_SKILL_API_FLAG must now be set to the full api_key value (e.g., pk_...:sk_...) exactly as returned.
- Revised the Python and Node.js client instructions: explicit dependency setup and usage of stateful thread_id for multi-turn conversations.
- Documented the expected handling and display of agent-run results, with clear rules on presenting links and plain text to users.
- Clarified paid history retrieval process, including precise pre-checks and endpoint usage.
v1.0.9
No file changes detected in this version.
- No updates or modifications were made; no changelog entries for this release.
- All features, interfaces, and step-by-step rules remain unchanged.
v1.0.8
Version 1.0.8 (prana-stock-scoring-analysis-v2)
- Added detailed process rules to enforce step-by-step execution, requiring explicit user confirmation before issuing or updating API keys and setting environment variables.
- Clarified that every `api_key` is unique to each issuance and must not be overwritten or refreshed without explicit user permission.
- Step 2 (API key acquisition & environment setup) cannot be run in part or out of sequence; it is now a mandatory, triple-confirmed sequence.
- Updated instructions and confirmation requirements for environment variable handling, making distinctions between session and global environment more explicit.
- Strengthened output rules: never auto-correct, refresh, or retry without user instruction; always present links as clickable.
- Restricted history/record API calls to explicit user request only; not invoked as part of the standard flow.
v1.0.7
- No changes detected in this version; content and functionality remain the same.
- SKILL.md is unchanged from the previous release.
v1.0.6
Version 1.0.6
- 场景描述优化,更聚焦于A股投研场景和多维度数据分析用途。
- 运行流程部分补充禁止命令行内赋值/合并的明确说明,并简化脚本参数说明。
- 明确用户输出时对“网页链接呈现”、“预期内 JSON 展示”、“达到尝试上限”等场景给出精细操作要求。
- 示例请求语句/参数和流程更精炼,提升可读性和执行指引准确性。
- 其他用语调整,提升易用性和合规性。
v1.0.5
prana-stock-scoring-analysis-v2 v1.0.5
- 优化了技能描述和使用场景表述,使其更贴合投研应用。
- 规范了终端命令中禁止使用环境变量设置的说明,强调安全用法。
- Node.js 和 Python 脚本参数示例更新,体现一致性和安全要求。
- 细化了用户输出结果时的链接呈现方式说明,提升用户体验。
- 未涉及功能逻辑或接口变更。
v1.0.4
- 明确技能定位为多维度A股深度分析,新增分析报告输出说明。
- 环境变量 PRANA_SKILL_API_FLAG 说明升级,客户端脚本不再支持自动获取密钥,需宿主方提前设置。
- 禁止在脚本命令前直接赋值密钥,强调安全执行方式。
- 新增脚本输出中链接展示规范,要求为用户可直接点击的格式。
- 进一步细化接入指引,对常见使用场景和命令调用细节做出补充与规范。
v1.0.3
Version 1.0.3 Changelog
- Clarified user consent requirements before writing environment variables, including explicit handling if the user does not agree to global configuration.
- Updated the method for retrieving Prana API keys to use the GET method (correction in the network_requests schema).
- Added strong restrictions on calling the skill-purchase-history-url API: only invoke on explicit user request regarding history or records.
- Improved documentation wording to highlight privacy and user intent controls.
- No code or core logic changes were made.
v1.0.2
Version 1.0.2
- Simplified and streamlined documentation to focus on required environment variables and API calls.
- Clarified the step-by-step process for skill initialization, operation, and history retrieval.
- Updated environment variable and API key instructions for improved clarity.
- Provided concise command examples for both Node.js and Python usage.
- Added a section outlining security and audit details for remote agent execution.
- Removed previous detailed workflow and implementation notes, focusing on integration essentials.
v1.0.1
- No user-visible changes in this version.
- Documentation, code, and configuration remain unchanged.
v1.0.0
- Initial release of A股多维度深度分析skill.
- Provides comprehensive analysis of China A-shares stocks across fundamentals, technicals, and institutional trends.
- Generates interactive HTML analysis reports to help investors understand key stock indicators.
- Supports both Node.js (default) and Python 3 clients for flexible execution.
- Includes environment variable and API key configuration steps for secure usage.
- Offers a feature to retrieve historical payment records via a dedicated browser link.
Metadata
Frequently Asked Questions
What is prana-stock-scoring-analysis-v2?
通过调用 Prana 平台上的远程 agent 完成以下处理:通过基本面、技术面、机构动向等多个维度对股票进行数据深度分析,生成交互式HTML分析报告。帮助投资者多方面了解股票的各项指标和数据。 IMPORTANT: This skill has a mandatory step-by-step process.... It is an AI Agent Skill for Claude Code / OpenClaw, with 232 downloads so far.
How do I install prana-stock-scoring-analysis-v2?
Run "/install prana-stock-scoring-analysis-v2" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is prana-stock-scoring-analysis-v2 free?
Yes, prana-stock-scoring-analysis-v2 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does prana-stock-scoring-analysis-v2 support?
prana-stock-scoring-analysis-v2 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created prana-stock-scoring-analysis-v2?
It is built and maintained by goCyberTrade (@gocybertrade); the current version is v1.0.13.
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