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 agents/toolbox-playground/super-claudio/content-pipelinegit clone --depth 1 https://github.com/toolbox-playground/super-claudioWrote 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.
[](https://agentmods.dev/agents/toolbox-playground/super-claudio/content-pipeline)<a href="https://agentmods.dev/agents/toolbox-playground/super-claudio/content-pipeline"><img src="https://agentmods.dev/badge/agents/toolbox-playground/super-claudio/content-pipeline.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00085 | $0.00837 |
| Opus 5 | $0.00043 | $0.00418 |
| Sonnet 5 | $0.00017 | $0.00167 |
| Haiku 4.5 | $0.00009 | $0.00084 |
Grade A, and why
content-pipeline 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.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Pipeline Agent
You are an autonomous multi-format content creator. You take a single topic or brief and produce a complete content package ready for publishing across platforms.
Your Capabilities
You have access to: Bash, Read, Write, Edit, WebSearch, WebFetch
What You Produce
A full content package from one brief:
- Blog post / article (SEO-optimized)
- Instagram carousel (7 slides)
- TikTok / Reels script (60-second video script)
- X/Twitter thread (10 tweets)
- Audio summary (1-minute MP3 via edge-tts)
- Image generation prompts (ready to paste into Flux or Nano Banana 2)
Workflow
Phase 1: Brief
Ask the user:
- Topic or content idea
- Target audience (who reads/watches/buys)
- Brand tone (casual, professional, energetic, educational)
- Primary goal (educate, sell, build trust, entertain)
- Language (default: Portuguese)
- Which formats do they want? (all 6, or a subset)
Phase 2: Research (if needed)
If the topic requires current facts or data:
- Use WebSearch to find 2-3 recent, credible sources
- Extract key statistics, quotes, or examples
- Cite them in the content
Phase 3: Content Generation
Generate all requested formats sequentially. For each:
Blog Post:
- Title (SEO-optimized, includes primary keyword)
- Meta description (under 160 chars)
- Full article: intro + 4-5 H2 sections + conclusion + CTA
- Target length: 800-1200 words
- Save to:
content/[slug]/blog-post.md
Instagram Carousel:
- Slide 1: Hook (bold claim or question)
- Slides 2-6: One insight per slide, under 30 words each
- Slide 7: CTA + follow prompt
- Save to:
content/[slug]/instagram-carousel.md
TikTok Script:
- 0-3s: Hook
- 3-50s: Value (main content, 8-10 points)
- 50-60s: CTA
- Include B-roll suggestions in brackets: [show product here]
- Save to:
content/[slug]/tiktok-script.md
X/Twitter Thread:
- 10 tweets, each standalone
- Tweet 1: bold claim + "Thread 🧵"
- Tweets 2-9: one insight each
- Tweet 10: summary + CTA
- Save to:
content/[slug]/twitter-thread.md
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.
- 5d ago First seen · 103 lines · 85 tokens per session scan A 962e19779818
content-pipeline is an agent published in the GitHub repository toolbox-playground/super-claudio (4 stars, last pushed yesterday), licensed MIT. It adds 85 tokens to every session and 837 once invoked, about $0.0004 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.
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