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us-stock-prediction

美股个股次日走势预测 skill。当用户输入美股股票代码(如 AAPL、TSLA)或公司名称(如 "苹果"、"特斯拉"),并要求预测次日(T+1)走势、给出交易计划、评估盈亏概率时,触发本 skill。skill 会用 mcp__MiniMax__web_search 搜证盘前 90 分钟的关键信息(财报、盘后走势、隔夜期货、期权异动、内部人交易、宏观日历等),按"五维分析框架"(基本面/技术面/资金面/情绪面/宏观面)交叉验证,产出可量化的方向预测(涨/跌/横盘 + 概率百分比 + 区间),并写入当前项目 markdown 目录下的 `us-stock-{TICKER}-{YYYY-MM-DD}.md`。输出必须有完整的逻辑推导链(每一维的打分过程与数据来源)、术语通俗解释、mermaid/ascii 流程图或可视化图表。适用场景:盘前/盘中想做次日的方向判断与交易计划;不适用:长线基本面估值(应改用 finance 领域其他 skill)、日内高频交易、加密货币/港股/A股。

75

Quality

92%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable and well-sequenced with strong validation feedback loops and clean one-level-deep progressive disclosure. Its main weakness is conciseness: several warnings and example tables are restated multiple times and could be consolidated without losing clarity.

Suggestions

Consolidate the repeated '≥70% direction probability must clamp to 65%' rule into a single canonical statement in 风险铁律 and reference it from 步骤4/反模式/自检清单 instead of restating it four times.

Trim the 反模式 table to the highest-value rows or move it into a reference file, since the risk rules and self-check list already cover most of the same anti-patterns.

Move the full markdown output skeleton (步骤6) into references/output-template.md (which already exists) and keep only a short structural summary inline, reducing body length.

DimensionReasoningScore

Conciseness

Content is mostly efficient and avoids explaining basics Claude knows, but ~345 lines with repeated warnings (the '≥70% clamp to 65%' rule is restated 4+ times across 步骤4/风险铁律/反模式/自检清单) and large example/anti-pattern tables that could be tightened; noticeable padding rather than severe verbosity.

3 / 5

Actionability

Fully executable guidance — concrete search-query strings, a -2~+2 scoring table with examples, the position-sizing formula '仓位(股数) = (账户净值 × 风险预算%) ÷ (入场价 − 止损价)', a copy-paste markdown skeleton, and mermaid/ascii chart examples covering common cases.

5 / 5

Workflow Clarity

A clearly sequenced 7-step workflow with an ASCII flow diagram and explicit validation/feedback checkpoints — 搜证失败→降级置信度, 对冲信号→强制降级, a 反模式 table, and a交付前自检清单 with '未通过任何一项=重新写' — matching the anchor for explicit validation and checklists.

5 / 5

Progressive Disclosure

SKILL.md is an overview; detailed material is split one level deep into four real, clearly signaled reference files (five-dimension-framework, terminology, output-template, search-queries), each described in 资源引用 with a '先Read它再继续' navigation hint — easy to navigate, no nested references.

5 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is concrete, trigger-rich, and clearly bounded: it names specific actions, natural trigger terms in both languages, explicit use/non-use scenarios, and a distinct niche. It is long but every clause carries load.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — '搜证盘前90分钟的关键信息(财报、盘后走势、隔夜期货、期权异动、内部人交易、宏观日历)', '按五维分析框架交叉验证', '产出可量化的方向预测(涨/跌/横盘+概率百分比+区间)', '写入…markdown目录' — comprehensive coverage.

5 / 5

Completeness

Explicitly answers both 'what' (搜证、五维交叉验证、量化方向预测、写入markdown) and 'when' ('触发本skill' trigger conditions plus a clear 适用场景/不适用 boundary), matching the anchor for concrete trigger phrases.

5 / 5

Trigger Term Quality

Covers natural terms users would say across both languages — '美股股票代码(如AAPL、TSLA)', '公司名称(如苹果、特斯拉)', '预测次日(T+1)走势', '给出交易计划', '评估盈亏概率' — with synonyms and concrete ticker examples.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (美股个股次日T+1预测) and explicitly excludes overlapping domains — 长线估值、日内高频、加密/港股/A股 — minimizing conflict with adjacent finance skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
digoal/blog
Reviewed

Table of Contents

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