Token导航 LogoToken导航TokenDH.com
研究检索权限需确认github未标认证来源可访问许可证需确认审计通过

talk-stage3-concepts谈论 stage3 概念

Agent Skill

talk-stage3-concepts 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

599

周安装

24

GitHub Stars

3,992

下载量

194
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:talk-stage3-concepts(谈论 stage3 概念)
来源仓库:https://github.com/florianbruniaux/claude-code-ultimate-guide
仓库路径:skills/talk-stage3-concepts
安装命令:
npx skills add https://github.com/florianbruniaux/claude-code-ultimate-guide --skill talk-stage3-concepts
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/florianbruniaux/claude-code-ultimate-guide --skill talk-stage3-concepts

简介

talk-stage3-concepts 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围和维护状态,注意可能触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Talk Stage 3: Concepts

Builds an exhaustive catalogue of all identifiable concepts in the source material. Each concept is numbered, categorized, and scored for its talk potential.

When to Use This Skill

  • After Stage 1 (and Stage 2 if REX mode)
  • Before Stage 4 (Position needs the concept catalogue)
  • When you want a structured inventory of what's available before choosing an angle

What This Skill Does

  1. Reads the summary — loads {slug}-summary.md
  2. Reads the timeline (if available) — enriches scoring with verified dates
  3. Extracts concepts — full scan of the source material
  4. Categorizes — assigns each concept to a domain category
  5. Scores — HIGH / MEDIUM / LOW for talk potential
  6. Optional repo enrichment — if repo_path is provided, analyzes AI config concepts
  7. Writes output files

Input

  • talks/{YYYY}-{slug}-summary.md (required)
  • talks/{YYYY}-{slug}-timeline.md (optional — enriches REX concepts)
  • repo_path (optional — for config/infrastructure concept extraction)

Output

  • talks/{YYYY}-{slug}-concepts.md (main catalogue)
  • talks/{YYYY}-{slug}-concepts-enriched.md (if repo_path provided)

Scoring Criteria

HIGH — Strong potential

  • Demonstrable live or with a screenshot
  • Counter-intuitive or surprising (triggers a reaction)
  • Associated with verifiable numbers
  • Concrete and actionable (explainable in 30 seconds)
  • Differentiator vs other talks on the same topic

MEDIUM — Moderate potential

  • Useful but expected (not surprising)
  • Missing concrete proof or numbers
  • Too specific to one particular context
  • Needs too much explanation for a 30-min talk

LOW — Weak potential

  • Too abstract or philosophical without concrete grounding
  • Already heavily covered by other speakers
  • Requires specific technical background
  • Hard to illustrate in a slide

Scoring discipline: Max 30% HIGH. If everything is HIGH, nothing is.

Standard Categories

CategoryDescription
ArchitectureTechnical decisions, stack, structural patterns
ToolingTools, workflows, automations
PhilosophyPrinciples, mindsets, approaches
WorkflowWork processes, habits
Knowledge TransferOnboarding, team, knowledge sharing
ProblemsObstacles encountered, trade-offs
Open SourceContributions, sharing, community
AI ConfigAI configuration, profiles, knowledge feeding
AI InfrastructureAgents, skills, hooks, commands
AI QualityReview, tests, anti-patterns
AI SecuritySecurity hooks, guardrails
OptimizationPerformance, cost/token reduction

Adapt or create categories if the talk has domain-specific areas.

Output Format

concepts.md

# Key Concepts — {provisional title}

**Date**: {date}
**Source**: {source path} × Summary × Timeline (if available)

---

## Concept table

| # | Concept | Category | Short description | Talk potential |
|---|---------|----------|------------------|----------------|
| 1 | **{Concept name}** | {Category} | {1-2 concrete sentences} | HIGH / MEDIUM / LOW |
...

---

## Category breakdown

| Category | Count | HIGH concepts | Examples |
|----------|-------|---------------|---------|
| {category} | {n} | {n} | {examples} |
...
| **TOTAL** | **{N}** | **{N HIGH}** | |

---

## Recommendations for positioning

{3-5 sentences on concept clusters that could form the talk's acts.
Which HIGH concepts reinforce each other? What narrative arc is emerging?}

concepts-enriched.md (if repo available)

Same structure but focused on what the repo analysis reveals:

  • Specialized agents (count, size, roles)
  • Invocable skills (catalogue, domains covered)
  • System hooks (events, logic)
  • Modular config (profiles, modules, pipeline)
  • Project-specific code patterns

For each enriched concept, include:

  • Exact source: file and approximate line
  • Demo-able: yes/no (can it be shown in a slide or live?)

Anti-patterns

  • Creating overly granular concepts (one feature = one concept max)
  • Scoring HIGH by default — be selective
  • Omitting LOW concepts (they're useful in positioning as "angles to avoid")
  • Duplicating very similar concepts (merge them instead)
  • Analyzing repo code if the repo isn't accessible

Validation Checklist

  • Minimum 15 concepts identified (20+ for REX with repo)
  • Each concept has a 1-2 sentence concrete description
  • Scores are calibrated (not all HIGH, not all LOW)
  • Categories cover the summary's themes
  • Positioning recommendations present
  • Files saved to correct paths

Tips

  • The concept catalogue is what Stage 4 (Position) draws from — the richer it is, the better the angle choices
  • LOW concepts are valuable: they define the boundaries of what NOT to put in the talk
  • If two concepts feel very similar, merge them — a smaller, sharper list beats a long diluted one

Related

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

38.99%
按下载量换算76

Claude

27%
按下载量换算52

Cursor

19.52%
按下载量换算38

Gemini CLI

9.96%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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