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.
npx agentmods add skills/nirholas/xactions/content-repurposingnpx skills add nirholas/XActions --skill content-repurposinggit clone --depth 1 https://github.com/nirholas/XActionsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.00907 |
| Opus 5 | $0.00031 | $0.00453 |
| Sonnet 5 | $0.00012 | $0.00181 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
content-repurposing 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.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Repurposing
Browser scripts and MCP workflows for identifying top content and generating repurposed variations.
Script Selection
| Goal | File | Navigate to |
|---|---|---|
| Repurpose tweets (5 formats) | src/contentRepurposer.js |
x.com/USERNAME |
| Compose threads from ideas | src/threadComposer.js |
x.com/USERNAME |
| Content calendar analysis | src/contentCalendar.js |
x.com/USERNAME |
| Find top-performing content | src/tweetPerformance.js |
x.com/USERNAME |
| Optimize posting schedule | src/tweetScheduleOptimizer.js |
x.com/USERNAME |
Content Repurposer
File: src/contentRepurposer.js
The main repurposing engine. Scans your timeline, then converts any tweet into 5 content formats.
Controls
XActions.scan()-- Scrape tweets from current pageXActions.list()-- Show all scraped tweets with indicesXActions.toThread(i)-- Convert tweet to thread outlineXActions.toSummary(i)-- Condense to punchy summary variationsXActions.toStorm(i)-- Break into numbered tweet stormXActions.toBlog(i)-- Generate blog/article outline with SEO keywordsXActions.toQuoteTemplates(i)-- Create 3 quote-retweet variationsXActions.all(i)-- Run ALL 5 repurposing strategiesXActions.export()-- Download all repurposed content as JSON
Repurposing Formats
| Format | Best For | Output |
|---|---|---|
| Thread | Deep dives, tutorials | Hook + body parts + CTA |
| Summary | Time-sensitive repost | 3 punchy variations |
| Storm | Long content splitting | Numbered 1/N tweets |
| Blog | SEO content, articles | Title + sections + keywords |
| Quote Templates | Engagement farming | Agreement/personal/contrarian takes |
MCP Workflow
- Call
x_get_tweetswithlimit: 100for the target account - Call
x_get_profileto get follower count for rate calculation - Rank by engagement rate:
(likes + RTs + replies) / followers * 100 - For top 5, generate variations using the content repurposer patterns
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.
- 2d ago First seen · 90 lines · 62 tokens per session scan A 25fc5407efa5
content-repurposing is a skill published in the GitHub repository nirholas/XActions (496 stars, last pushed 5d ago), licensed Apache-2.0. It adds 62 tokens to every session and 907 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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