repurpose-talk

A content-repurposing skill that turns a delivered talk and its materials into outlines for blog posts, social posts, newsletter sections, and republication pitches. It creates directions and frameworks rather than finished drafts.

In plain words
What is it for?
It is for generating multiple content angles from a talk, using its title, abstract, script, speaker notes, or transcript.
Why use it?
It helps extend the reach of one presentation without forcing every new piece to be written from scratch. It also keeps the outputs grounded in the actual talk materials.

Skill for Claude CodeCodex

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/phazonoverload/devadvokit/repurpose-talk
Any agent
npx skills add phazonoverload/devadvokit --skill repurpose-talk
Clone the repo
git clone --depth 1 https://github.com/phazonoverload/devadvokit

Made for: Claude Code, Codex.

Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 966 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 $0.00060 $0.00966
Opus 5 $0.00030 $0.00483
Sonnet 5 $0.00012 $0.00193
Haiku 4.5 $0.00006 $0.00097

Measured 2d ago against content hash 4b28072318b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

repurpose-talk 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 2d 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.

skills/repurpose-talk/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Before doing anything else:

  1. Check if ~/.devadvokit.md exists.
  2. If it does, read it silently and use it throughout this skill.
  3. If it does not, stop and tell the user: "I need your DevRel context before I can run this skill. Please run /setup-devadvokit first."

What NOT to Do

This skill produces outlines, angles, and frameworks — not full drafts. Specifically:

  • No full blog posts — outlines only. Full drafts are scope creep and end up generic without heavy editing.
  • No video scripts — that's a different skill.
  • No SEO metadata — separate concern, different skill.

The goal is multiple content directions from one talk, not finished pieces. Editing produces the final versions.


Q&A

Ask these questions one at a time. Wait for each answer before asking the next.

  1. What's the talk title and abstract? (Paste or type — this is required. If you only have a title and need help with an abstract, say so and I'll help you draft one.)

  2. Do you have a script, speaker notes, or transcript? Paste it here or provide a file path. This allows me to ground outputs in your actual content rather than infering from the abstract alone. If you only have the abstract, I can still work with that.

  3. Who's the target audience for the repurposed content, and what's their familiarity level? (Beginner / practitioner / expert — this affects depth and terminology)

  4. What tone should the repurposed content have? (Technical and depth-focused? Conversational and approachable? Thought leadership and industry perspective?)

  5. What conference or event was this presented at, and when? (This gives context and provides "as I presented at X" framing for the repurposed content)


Quality Gates (if transcript/notes provided)

If transcript or notes were provided, process them before generating outputs:

  1. Pull 2–3 pull quotes — direct lines that work as standalone social copy. Memorable, quotable, out-of-context friendly.

  2. Flag demo or live content — anything that won't translate to written formats. Note what needs adaptation or removal.

Read the full file on GitHub · 98 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. 2d ago First seen · 98 lines · 60 tokens per session scan A 4b28072318b9

Subscribe to this mod's changes

repurpose-talk is a skill published in the GitHub repository phazonoverload/devadvokit (16 stars, last pushed 4mo ago), licensed MIT. It adds 60 tokens to every session and 966 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.

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