talk-stage1-extract
Extracts and structures source material (articles, transcripts, notes) into a talk summary with narrative arc, themes, metrics, and gaps. Auto-detects REX vs Concept type. Use when starting a new talk from any source material or auditing existing material before committing to a talk.
Best use case
talk-stage1-extract is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Extracts and structures source material (articles, transcripts, notes) into a talk summary with narrative arc, themes, metrics, and gaps. Auto-detects REX vs Concept type. Use when starting a new talk from any source material or auditing existing material before committing to a talk.
Teams using talk-stage1-extract should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/stage-1-extract/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How talk-stage1-extract Compares
| Feature / Agent | talk-stage1-extract | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Extracts and structures source material (articles, transcripts, notes) into a talk summary with narrative arc, themes, metrics, and gaps. Auto-detects REX vs Concept type. Use when starting a new talk from any source material or auditing existing material before committing to a talk.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Talk Stage 1: Extract
Transforms raw material (article, transcript, notes, or a mix) into a structured summary ready for the pipeline's downstream stages. Auto-detects source type.
## When to Use This Skill
- Starting a new talk from any source material
- First step of the talk pipeline (always run before other stages)
- Auditing existing source material before committing to a talk
## What This Skill Does
1. **Collects metadata** — asks for slug, event, date, duration, audience, mode if not provided
2. **Reads the source** — loads the source file or inline content
3. **Detects source type** — REX (real-world proof) vs Concept (ideas/thesis) based on content signals
4. **Extracts the narrative arc** — chronological for REX, thematic for Concept
5. **Extracts metrics** — every measurable number with its source
6. **Identifies main themes** — 3-7 themes
7. **Flags gaps** — what's missing for a complete talk
8. **Writes `{slug}-summary.md`**
## Input
Required:
- Source file path or inline content (article `.mdx`, transcript `.md`, notes)
- Metadata: `slug`, `event`, `date`, `duration`, `audience`, `type` (--rex or --concept)
If metadata is missing → `AskUserQuestion` before proceeding.
## Output
`talks/{YYYY}-{slug}-summary.md`
## Source Type Detection
| REX signals | Concept signals |
|-------------|-----------------|
| Specific dates | Theses, arguments |
| Measured metrics | General observations |
| Project/tool names | Trend observations |
| Commits, releases, PRs | Analogies, metaphors |
| "I shipped", "We built" | "I think", "In my opinion" |
If hybrid → note both components in the summary.
## Output Format
```markdown
# Talk Summary — {Provisional Title}
**Slug** : {slug}
**Event** : {event}
**Date** : {date}
**Duration** : {duration} min
**Audience** : {audience description}
**Type detected** : REX | Concept | Hybrid
**Source** : {source file path}
---
## Narrative Arc
{Arc description: 3-5 sentences. Chronological if REX, thematic if Concept.}
## Main Themes
| # | Theme | Short description | Weight |
|---|-------|------------------|--------|
| 1 | {theme} | {description} | High/Medium/Low |
...
## Key Metrics Extracted
{All measurable numbers found in the source}
Format: `{value}` — {context} — Source: {section/page/git}
Examples:
- `1,200 commits` over 7 months — Source: "acceleration" section
- `-97% traffic` after SSE migration — Source: CHANGELOG v1.1.0
If none → "No verifiable metrics found (Concept mode)"
## Narrative Potential
{3-5 sentences on the strengths and possible narrative angles.
What makes this talk potentially strong. What might be missing.}
## Gaps Identified
- [ ] {gap 1} — {how to fill it}
- [ ] {gap 2} — {how to fill it}
If no obvious gaps → "No major gaps identified."
## Recommendations for next stages
- **Research**: {recommended / not applicable (Concept mode)} — {why}
- **Concepts**: {priority themes to explore}
- **Position**: {angles already visible from the source material}
---
*Generated by talk-stage1-extract — {date}*
*Source: {source path}*
```
## Metric Extraction Rules
- Do not round without indicating it
- Always include the metric's source
- If two sources contradict → flag both, do not pick one
- No invented metrics to fill gaps
- Use `{before} → {after}` format for evolutions
## Anti-patterns
- Vague summary ("This text is about AI...")
- Omitting metrics — even approximate ones with their source
- Hiding gaps — naming them is better than pretending they don't exist
- Changing the detected type without justification
- Inventing a narrative arc not present in the source
## Validation Checklist
- [ ] Source type detected and justified
- [ ] Narrative arc in 3-5 clear sentences
- [ ] All measurable metrics extracted with their source
- [ ] Main themes listed (3-7 max)
- [ ] Gaps explicitly identified
- [ ] File saved to `talks/{YYYY}-{slug}-summary.md`
## Tips
- Run this before the orchestrator if you want to verify the source material is usable
- The summary is the foundation — every downstream stage reads it
- Hybrid sources (part REX, part Concept) are fine — name both components clearly
## Related
- [Stage 2: Research](../stage-2-research/SKILL.md) — git archaeology (REX mode)
- [Stage 3: Concepts](../stage-3-concepts/SKILL.md) — reads this summary
- [Orchestrator](../orchestrator/SKILL.md) — runs all stages in sequenceRelated Skills
talk-stage6-revision
Produces revision sheets with quick navigation by act, a master concept-to-URL table, Q&A cheat-sheet with 6-10 anticipated questions, glossary, and external resources list. Use when preparing for a talk with Q&A, creating shareable reference material for attendees, or building a safety-net glossary for live delivery.
talk-stage5-script
Produces a complete 5-act pitch with speaker notes, a slide-by-slide specification, and a ready-to-paste Kimi prompt for AI slide generation. Requires validated angle and title from Stage 4. Use when you have a confirmed talk angle and need the full script, slide spec, and AI-generated presentation prompt.
talk-stage4-position
Generates 3-4 strategic talk angles with strength/weakness analysis, title options, CFP descriptions, and a peer feedback draft, then enforces a mandatory CHECKPOINT for user confirmation before scripting. Use when deciding how to frame a talk, preparing a CFP submission, or choosing between multiple narrative angles.
talk-stage3-concepts
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.
talk-stage2-research
Performs git archaeology, changelog analysis, and builds a verified factual timeline by cross-referencing git history with source material. REX mode only — skipped automatically in Concept mode. Use when building a REX talk and you need verified commit metrics, release timelines, and contributor data from a git repository.
talk-pipeline
Orchestrates the complete talk preparation pipeline from raw material to revision sheets, running 6 stages in sequence with human-in-the-loop checkpoints for REX or Concept mode talks. Use when starting a new talk pipeline, resuming a pipeline from a specific stage, or running the full end-to-end preparation workflow.
voice-refine
Transform verbose voice input into structured, token-efficient Claude prompts. Use when cleaning up voice memos, dictation output, or speech-to-text transcriptions that contain filler words, repetitions, and unstructured thoughts.
skill-creator
Scaffold a new Claude Code skill with SKILL.md, frontmatter, and bundled resources. Use when creating a custom skill, standardizing skill structure across a team, or packaging a skill for distribution.
rtk-optimizer
Wrap high-verbosity shell commands with RTK to reduce token consumption. Use when running git log, git diff, cargo test, pytest, or other verbose CLI output that wastes context window tokens.
release-notes-generator
Generate release notes in 3 formats (CHANGELOG.md, PR body, Slack announcement) from git commits. Automatically categorizes changes and converts technical language to user-friendly messaging. Use for releases, changelogs, version notes, what's new summaries, or ship announcements.
pr-triage
4-phase PR backlog management with audit, deep code review, validated comments, and optional worktree setup. Use when triaging pull requests, catching up on pending code reviews, or managing a backlog of open PRs. Args: 'all' to review all, PR numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit only.
landing-page-generator
Generate complete, deploy-ready landing pages from any repository. Use when creating a homepage for an open-source project, building a project website, converting a README into a marketing page, or standardizing landing pages across multiple repos.