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hackathon-idea-scoring黑客马拉松创意评分

Agent Skill

hackathon-idea-scoring 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

569

周安装

23

GitHub Stars

1

下载量

178
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hackathon-idea-scoring(黑客马拉松创意评分)
来源仓库:https://github.com/bernieweb3/hackathon-ai-devkit
仓库路径:skills/hackathon-idea-scoring
安装命令:
npx skills add https://github.com/bernieweb3/hackathon-ai-devkit --skill hackathon-idea-scoring
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/bernieweb3/hackathon-ai-devkit --skill hackathon-idea-scoring

简介

用于处理 GitHub 仓库、Issue 和 Pull Request 信息,协助代码协作与变更管理。

  • 适合在需要围绕仓库状态或代码变更进行整理时使用,支持多宿主环境。
  • 通过 npx skills add 命令从指定仓库安装,具体用法请参考原始 README。
  • 安装前应确认权限范围、维护状态,并评估是否会触发联网或文件操作。
  • 注意:避免直接执行未经验证的命令,防止误改生产环境代码。

SKILL.md

hackathon-idea-scoring

Goal

Evaluate and rank candidate project ideas against a weighted scoring rubric aligned with hackathon judging criteria and team capabilities.


Trigger Conditions

Use this skill when:

  • A list of candidate ideas is available from hackathon-idea-generator
  • evaluation_axes from hackathon-track-analyzer are confirmed
  • The team must converge on a single idea before scoping begins
  • Objective comparison is needed to resolve disagreement between team members
  • Invoked directly after hackathon-idea-generator; output gates all subsequent phases

Inputs

InputTypeRequiredDescription
ideasobject[]YesIdeas list from hackathon-idea-generator
evaluation_axesobject[]YesScoring axes from hackathon-track-analyzer
team_skillsstring[]YesTechnologies and domains the team is proficient in
hackathon_duration_hoursintegerYesTotal hours available
team_sizeintegerYesNumber of team members
weightsobjectNoCustom weight overrides per evaluation axis

Outputs

OutputDescription
scored_ideasEach idea with scores per axis and total score
rankingOrdered list of ideas by total score
top_recommendationSingle recommended idea with rationale
risk_flagsConcerns for each top-3 idea
recommended_skillsSuggested next skills to invoke

Rules

  1. Score every idea on every evaluation axis using a 1–5 scale.
  2. Apply axis weights when computing total score; default weight is 1.0 if not specified.
  3. Apply a feasibility_penalty (-0.5 per axis point) if the team lacks skills required.
  4. Apply a time_penalty (-1.0) if the idea cannot realistically ship in hackathon_duration_hours.
  5. Surface at least one risk flag per top-3 idea.
  6. Select top_recommendation based on highest adjusted total score.
  7. Break ties in favor of the idea with the highest feasibility score.

Output Format

scored_ideas:
  - id: "<idea-N>"
    title: "<title>"
    scores:
      - axis: "<axis name>"
        score: <1-5>
        notes: "<rationale>"
    penalties:
      - type: "<feasibility|time>"
        value: <number>
    total_score: <number>

ranking:
  - rank: <number>
    id: "<idea-N>"
    total_score: <number>

top_recommendation:
  id: "<idea-N>"
  title: "<title>"
  rationale: "<string>"

risk_flags:
  - id: "<idea-N>"
    risks:
      - "<risk>"

recommended_skills:
  - "<skill-name>"

Example

Input:

ideas:
  - id: "idea-1"
    title: "AnchorAI"
    risk_level: "medium"
  - id: "idea-3"
    title: "CalmDraft"
    risk_level: "low"
evaluation_axes:
  - axis: "Innovation"
    weight: 1.5
  - axis: "Impact"
    weight: 1.5
  - axis: "Technical Execution"
    weight: 1.0
team_skills: ["Python", "React", "OpenAI API"]
hackathon_duration_hours: 24
team_size: 3

Output:

scored_ideas:
  - id: "idea-1"
    title: "AnchorAI"
    scores:
      - axis: "Innovation"
        score: 4
        notes: "Memory layer is novel; similar products exist but not for this audience"
      - axis: "Impact"
        score: 5
        notes: "Addresses acute unmet need at scale"
      - axis: "Technical Execution"
        score: 3
        notes: "Memory persistence adds integration complexity"
    penalties: []
    total_score: 17.5

  - id: "idea-3"
    title: "CalmDraft"
    scores:
      - axis: "Innovation"
        score: 3
        notes: "CBT journaling apps exist; GPT reframing is incremental"
      - axis: "Impact"
        score: 4
        notes: "Reaches self-directed users effectively"
      - axis: "Technical Execution"
        score: 5
        notes: "Well within team skills; highly shippable in 24h"
    penalties: []
    total_score: 16.5

ranking:
  - rank: 1
    id: "idea-1"
    total_score: 17.5
  - rank: 2
    id: "idea-3"
    total_score: 16.5

top_recommendation:
  id: "idea-1"
  title: "AnchorAI"
  rationale: "Highest combined score on weighted innovation and impact axes; team has required skills."

risk_flags:
  - id: "idea-1"
    risks:
      - "Memory persistence implementation may exceed time budget if OpenAI context window approach is chosen"

recommended_skills:
  - "hackathon-scope-cutter"

Context Files

Knowledge Base

  • knowledge/hackathon-judging-criteria.md
  • knowledge/hackathon-winning-patterns.md
  • knowledge/hackathon-mvp-strategy.md
  • knowledge/hackathon-common-failures.md

Playbooks

  • playbooks/hackathon-workflow.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.02%
按下载量换算64

Claude

27.91%
按下载量换算50

Cursor

17.27%
按下载量换算31

Gemini CLI

9.22%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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