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ls569333469

Meme Signal Evaluator

作者 xueqiu · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ⚠ suspicious
223
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install meme-signal-evaluator
功能描述
6-dimensional scoring engine for meme tokens with automated paper trading simulation. Use this skill when users ask to evaluate/score meme tokens, set up buy...
安全使用建议
This skill appears to be a high-level scoring and paper-trading design rather than a ready-to-run integration. Before installing or using it: 1) Ask the author (or vendor) for the concrete data sources/endpoints and whether you need API keys or paid subscriptions for Token Dynamic, Smart Money feeds, Topic Rush, Social Hype, etc. 2) Do not paste API keys or secrets into the skill without knowing exactly where they will be stored/used — the SKILL.md does not declare required env vars or where credentials would live. 3) If you plan to let the agent execute trades (even paper trades), confirm network access, logging, and how trade records are stored; run initial tests in a sandboxed environment. 4) Prefer skills with a clear source repo, documentation, and explicit list of required credentials; absence of provenance increases risk. Providing that additional information (source code or explicit integration instructions and required env vars) would raise confidence.
功能分析
Type: OpenClaw Skill Name: meme-signal-evaluator Version: 0.1.0 The skill bundle defines a comprehensive logic for a meme token scoring engine and paper trading simulator. The instructions in SKILL.md outline a systematic 6-dimensional evaluation process (Smart Money, Social, Trend, Inflow, KOL, and Hype) and include defensive measures such as penalties for honeypots or high-risk tokens. There is no evidence of malicious intent, data exfiltration, or prompt injection designed to compromise the agent or the host system.
能力评估
Purpose & Capability
The SKILL.md describes a coherent 6-dimension scoring engine and paper-trading simulation that aligns with the name/description. However, it repeatedly references external services (Token Dynamic API fields, Smart Money signals, Social Hype Leaderboard, Topic Rush, Meme Exclusive ranking, etc.) that are necessary for the stated functionality but the skill declares no required environment variables, endpoints, or credentials. That omission is unexpected and reduces clarity about how the skill would actually obtain needed data.
Instruction Scope
The runtime instructions stay within the stated domain: scoring tokens, strategy matching, and paper trading. They do not instruct the agent to read arbitrary local files, system configs, or other unrelated secrets. The SKILL.md is algorithmic and high-level rather than giving concrete commands; the main problem is vagueness about how external data is fetched and where results are transmitted.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, which is the lowest-risk install model. Nothing is written to disk by an installer.
Credentials
The skill implies heavy use of multiple third-party data providers/APIs, which in practice typically require API keys or paid access. Yet requires.env and primary credential are empty. That mismatch could mean the skill expects the platform to supply those feeds (not documented), or it will prompt for credentials at runtime — both are important to clarify. The absence of declared credentials is disproportionate to the number of external services referenced.
Persistence & Privilege
The skill does not request always:true, does not declare any install-time persistence, and does not instruct modification of other skills or system-wide settings. Autonomous invocation is allowed (platform default) but not combined with other red flags.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install meme-signal-evaluator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /meme-signal-evaluator 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
Initial release of meme-signal-evaluator - Implements a 6-dimensional scoring engine for meme token evaluation (Smart Money, Social, Trend, Inflow, KOL/Whale, Hype). - Supports automated paper trading simulation with configurable take profit, stop loss, and max hold time. - Allows for flexible strategy creation, matching tokens to buy triggers based on custom thresholds and weights. - Manages a watchlist with token lifecycle tracking from watching to sold/dismissed. - Provides performance tracking with metrics like win rate and average P&L per strategy. - Includes penalties for negative signals such as audit risks or high tax tokens.
元数据
Slug meme-signal-evaluator
版本 0.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Meme Signal Evaluator 是什么?

6-dimensional scoring engine for meme tokens with automated paper trading simulation. Use this skill when users ask to evaluate/score meme tokens, set up buy... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 223 次。

如何安装 Meme Signal Evaluator?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install meme-signal-evaluator」即可一键安装,无需额外配置。

Meme Signal Evaluator 是免费的吗?

是的,Meme Signal Evaluator 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Meme Signal Evaluator 支持哪些平台?

Meme Signal Evaluator 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Meme Signal Evaluator?

由 xueqiu(@ls569333469)开发并维护,当前版本 v0.1.0。

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