repurposing-content

repurposing-content is a skill for Claude Code, Codex from WesleySmits/agent-skills. It costs 43 tokens per session (2,681 once invoked), scanned A, original, no licence file.

A content-repurposing skill that turns one piece of content into several versions for different platforms. Repurposing means adapting the same core material to new formats or audiences.

In plain words
What is it for?
Use it to split blog content or other source material into social posts and other platform-specific formats.
Why use it?
It removes the need to rewrite each platform's content from scratch.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

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/wesleysmits/agent-skills/content-repurposing-engine
Any agent
npx skills add WesleySmits/agent-skills --skill content-repurposing-engine
Clone the repo
git clone --depth 1 https://github.com/WesleySmits/agent-skills

Made for: Claude Code, Codex.

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 repurposing-content

README.md
[![agentmods](https://agentmods.dev/badge/skills/wesleysmits/agent-skills/content-repurposing-engine.svg)](https://agentmods.dev/skills/wesleysmits/agent-skills/content-repurposing-engine)
Your own site
<a href="https://agentmods.dev/skills/wesleysmits/agent-skills/content-repurposing-engine"><img src="https://agentmods.dev/badge/skills/wesleysmits/agent-skills/content-repurposing-engine.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,681 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 5.1 $0.00043 $0.02681
Opus 5 $0.00022 $0.01340
Sonnet 5 $0.00009 $0.00536
Haiku 4.5 $0.00004 $0.00268

Measured 6d ago against content hash 21edc024ad84, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

repurposing-content 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 6d 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.

.agent/skills/content-repurposing-engine/SKILL.md · 482 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 6d ago First seen · 482 lines · 43 tokens per session scan A 21edc024ad84

Subscribe to this mod's changes

repurposing-content is a skill published in the GitHub repository WesleySmits/agent-skills (6 stars, last pushed 7mo ago), with no licence file. It adds 43 tokens to every session and 2,681 once invoked, about $0.0002 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 2026-08-31.

Related

Other skills, from other repositories

agent-payment-x402

Add x402 payment execution to AI agents — per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents need to pay for APIs, services, or other agents.

sifxprime/kodelyth-ecc · 47 tokens

browser-qa

Use this skill to automate visual testing and UI interaction verification using browser automation after deploying features.

sifxprime/kodelyth-ecc · 22 tokens

operating-coding-change

The single Rootloom entry for code changes. Route Direct, Scoped, Governed, Evidence, and external-action work; repair owning invariants, preserve unrelated work, and report only verification that ran.

qingye-lab/rootloom · 46 tokens

setup-rootloom

Plan, install, inspect, update, or roll back Rootloom Personal Core in a user's Codex home. Supports Skills-only, guidance, and the recommended personal preset. Use when the user explicitly asks for a Rootloom setup plan, installation, configuration, bootstrap, repair, audit, status, update, reduction, rollback, or…

qingye-lab/rootloom · 87 tokens

project-guidance

Seed, refresh, refine, or validate concise evidence-backed AGENTS.md guidance. Deterministic scripts own the managed block; model judgment may add only durable repository-specific invariants outside it.

qingye-lab/rootloom · 42 tokens

operating-code-review

Review code, diffs, pull requests, migrations, or architecture without modifying files. Lead with severity-ranked evidence-backed findings, challenge root-cause claims, and disclose cleared and unreviewed scope.

qingye-lab/rootloom · 45 tokens