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talk-stage3-concepts

Turn a talk summary and optional timeline into a numbered, categorized catalogue of ideas. Rate each idea's presentation potential and receive suggestions for grouping strong concepts into a talk structure before choosing an angle.

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Builds a numbered, categorized concept catalogue from the talk summary and timeline, scoring each concept HIGH / MEDIUM / LOW for talk potential with optional repo enrichment. Use when you need a structured inventory of concepts before choosing a talk angle, or when assessing which ideas have the strongest presentation potential.

查看安装方法

适用场景

  • Listing ideas before choosing a talk angle
  • Comparing concepts for demonstrations and concrete evidence
  • Grouping related ideas into a talk structure
  • Finding additional talk material in accessible AI configuration files

包含的文件(1)

  • SKILL.md5.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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} x Summary x 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)

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