Token导航 LogoToken导航TokenDH.com
前端设计需要联网github未标认证来源可访问许可证需确认审计通过

hackathon-task-planner黑客马拉松任务计划

Agent Skill

hackathon-task-planner 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

428

周安装

18

GitHub Stars

1

下载量

150
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-task-planner(黑客马拉松任务计划)
来源仓库:https://github.com/bernieweb3/hackathon-ai-devkit
仓库路径:skills/hackathon-task-planner
安装命令:
npx skills add https://github.com/bernieweb3/hackathon-ai-devkit --skill hackathon-task-planner
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-task-planner

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-task-planner

Goal

Decompose the MVP scope into a sequenced, time-boxed task list with assigned roles and clear dependencies for execution during the hackathon.


Trigger Conditions

Use this skill when:

  • MVP features with time budgets are available from hackathon-scope-cutter
  • The team needs a structured task list before coding begins
  • Roles and parallel workstreams need to be defined
  • The critical path must be identified to protect the demo timeline
  • Invoked once per project during Phase 4; re-invoke if scope is cut during implementation

Inputs

InputTypeRequiredDescription
mvp_featuresobject[]YesMVP features with time budgets from hackathon-scope-cutter
tech_stackstring[]YesTechnologies being used
team_sizeintegerYesNumber of team members
team_rolesstring[]NoRole labels (e.g., frontend, backend, ML, design)
hackathon_duration_hoursintegerYesTotal hours available
start_offset_hoursintegerNoHours already elapsed since hackathon start (default: 0)

Outputs

OutputDescription
tasksFull task list with estimates, roles, and dependencies
critical_pathOrdered sequence of tasks that gate project completion
milestonesKey checkpoints with target hour marks
parallel_tracksTask groups that can be worked simultaneously
buffer_hoursHours reserved for integration, polish, and debugging
recommended_skillsSuggested next skills to invoke

Rules

  1. Decompose every MVP feature into tasks of 30 minutes to 3 hours each.
  2. Include setup, integration, and deployment tasks explicitly.
  3. Assign each task to exactly one role from team_roles (or "any" if unspecified).
  4. Identify the critical path as the longest dependency chain.
  5. Reserve buffer_hours = 15% of remaining hackathon time minimum.
  6. Order milestones at 25%, 50%, 75%, and 90% of remaining time.
  7. Flag any task without a clear owner as [UNASSIGNED].

Output Format

tasks:
  - id: "T-<number>"
    title: "<task title>"
    feature: "<parent feature>"
    role: "<role|[UNASSIGNED]>"
    estimated_hours: <number>
    depends_on:
      - "T-<number>"

critical_path:
  - "T-<number>"

milestones:
  - name: "<milestone name>"
    target_hour: <number>
    deliverable: "<what must exist>"

parallel_tracks:
  - track: "<track name>"
    tasks:
      - "T-<number>"

buffer_hours: <number>

recommended_skills:
  - "<skill-name>"

Example

Input:

mvp_features:
  - feature: "GPT-4 check-in conversation"
    estimated_hours: 4
  - feature: "Session memory (Redis)"
    estimated_hours: 5
  - feature: "Crisis escalation (mocked)"
    estimated_hours: 1
tech_stack: ["Python", "FastAPI", "React", "OpenAI API", "Redis"]
team_size: 3
team_roles: ["backend", "frontend", "fullstack"]
hackathon_duration_hours: 24
start_offset_hours: 2

Output:

tasks:
  - id: "T-01"
    title: "Set up FastAPI project and Redis"
    feature: "Session memory"
    role: "backend"
    estimated_hours: 1
    depends_on: []
  - id: "T-02"
    title: "Implement OpenAI chat endpoint"
    feature: "GPT-4 check-in conversation"
    role: "backend"
    estimated_hours: 2
    depends_on: ["T-01"]
  - id: "T-03"
    title: "Implement session memory read/write"
    feature: "Session memory"
    role: "backend"
    estimated_hours: 3
    depends_on: ["T-01"]
  - id: "T-04"
    title: "Build chat UI component"
    feature: "GPT-4 check-in conversation"
    role: "frontend"
    estimated_hours: 3
    depends_on: []
  - id: "T-05"
    title: "Wire frontend to chat API"
    feature: "GPT-4 check-in conversation"
    role: "fullstack"
    estimated_hours: 1
    depends_on: ["T-02", "T-04"]
  - id: "T-06"
    title: "Add crisis card component (mocked)"
    feature: "Crisis escalation"
    role: "frontend"
    estimated_hours: 1
    depends_on: ["T-04"]

critical_path:
  - "T-01"
  - "T-02"
  - "T-05"

milestones:
  - name: "Backend skeleton live"
    target_hour: 7
    deliverable: "FastAPI + Redis running; chat endpoint returns GPT-4 response"
  - name: "Frontend connected"
    target_hour: 11
    deliverable: "Chat UI communicates with backend end-to-end"
  - name: "Memory working"
    target_hour: 16
    deliverable: "AI recalls previous session context in demo flow"
  - name: "Demo-ready"
    target_hour: 19
    deliverable: "Full demo flow runs cleanly 3× in a row"

parallel_tracks:
  - track: "Backend"
    tasks: ["T-01", "T-02", "T-03"]
  - track: "Frontend"
    tasks: ["T-04", "T-06"]

buffer_hours: 3.3

recommended_skills:
  - "hackathon-code-implementer"

Context Files

Knowledge Base

  • knowledge/hackathon-mvp-strategy.md
  • knowledge/hackathon-reference-architecture.md
  • knowledge/hackathon-common-failures.md
  • knowledge/hackathon-tools.md

Playbooks

  • playbooks/hackathon-workflow.md
  • playbooks/24h-hackathon-playbook.md
  • playbooks/36h-hackathon-playbook.md
  • playbooks/48h-hackathon-playbook.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

按任务关键词查找相关 Skills

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

35.4%
按下载量换算53

Claude

30.47%
按下载量换算46

Cursor

16.35%
按下载量换算25

Gemini CLI

9.32%
按下载量换算14

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

继续浏览同类 Skills