talk-stage1-extract

talk-stage1-extract is a skill for Claude Code, Codex from FlorianBruniaux/claude-code-plugins. It costs 64 tokens per session (1,187 once invoked), scanned A, original, MIT.

A tool that turns articles, transcripts, or notes into a structured talk summary with a story arc, themes, measurements, and missing information.

In plain words
What is it for?
Use it when starting or reviewing a talk based on written material, recorded speech, or personal notes.
Why use it?
It organizes raw material before you commit to a presentation and shows what evidence or context is still absent.

Skill for Claude CodeCodex

Part of the ai-methodology plugin — 17 skills, 4 commands, 2 agents, 1 hook shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/florianbruniaux/claude-code-plugins/stage-1-extract
Any agent
npx skills add FlorianBruniaux/claude-code-plugins --skill stage-1-extract
Clone the repo
git clone --depth 1 https://github.com/FlorianBruniaux/claude-code-plugins

Made for: Claude Code, Codex.

Or install ai-methodology, the plugin that ships this one along with the rest of its 17 skills, 4 commands, 2 agents, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for talk-stage1-extract

README.md
[![agentmods](https://agentmods.dev/badge/skills/florianbruniaux/claude-code-plugins/stage-1-extract.svg)](https://agentmods.dev/skills/florianbruniaux/claude-code-plugins/stage-1-extract)
Your own site
<a href="https://agentmods.dev/skills/florianbruniaux/claude-code-plugins/stage-1-extract"><img src="https://agentmods.dev/badge/skills/florianbruniaux/claude-code-plugins/stage-1-extract.svg" alt="Measured on agentmods" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,187 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00064 $0.01187
Opus 5 $0.00032 $0.00593
Sonnet 5 $0.00013 $0.00237
Haiku 4.5 $0.00006 $0.00119

Measured 5d ago against content hash fc790a1c2c8d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

talk-stage1-extract scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/ai-methodology/skills/talk-pipeline/stage-1-extract/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 by asking for slug, event, date, duration, audience, mode if not provided
  2. Reads the source and loads the source file or inline content
  3. Detects source type (REX with real-world proof vs Concept with ideas/thesis) based on content signals
  4. Extracts the narrative arc (chronological for REX, thematic for Concept)
  5. Extracts metrics with every measurable number and 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

# 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}*

Read the full file on GitHub · 151 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 151 lines · 64 tokens per session scan A fc790a1c2c8d

Subscribe to this mod's changes

talk-stage1-extract is a skill published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 3d ago), licensed MIT. It adds 64 tokens to every session and 1,187 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

vc-autopilot

Emit and validate the provisional goal block for Autopilot Mode. Owns the 9-field format and resume detection from a pasted goal block.

withkynam/vibecode-pro-max-kit · 34 tokens

vc-problem-solving

Apply systematic problem-solving techniques when stuck. Use for complexity spirals, innovation blocks, recurring patterns, assumption constraints, simplification cascades, scale uncertainty.

withkynam/vibecode-pro-max-kit · 36 tokens

thoroughness-scoring

Score every decision point with a Thoroughness Rating (1-10). AI makes the marginal cost of doing things properly near-zero — pick the higher-rated option every time. Includes scope checks to distinguish contained vs unbounded work.

rohitg00/pro-workflow · 51 tokens

report

Read the delivery log and say which rules actually fire, which never have, and what to prune or fix. Use when the user asks whether ballast is doing anything, wants to clean up their rule catalog, or on a periodic review.

svy04/ballast · 49 tokens

orchestrate

Wire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.

rohitg00/pro-workflow · 30 tokens

squid-self-improve

Analyze developer corrections from the current coding session and persist lessons learned as rules in AGENTS.md files or memory. Use at the end of a session after the developer corrected your work, when they say "squid-self-improve", ask to capture what was learned, or ask you to reflect on mistakes and extract…

iusztinpaul/squid · 73 tokens