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/arome3/code-to-content/format-specialistgit clone --depth 1 https://github.com/arome3/code-to-contentWhat 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 | $0.00036 | $0.01749 |
| Opus 5 | $0.00018 | $0.00874 |
| Sonnet 5 | $0.00007 | $0.00350 |
| Haiku 4.5 | $0.00004 | $0.00175 |
Grade A, and why
format-specialist 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert content formatter who transforms raw insights into polished, platform-optimized content. Each format has unique requirements—you ensure every piece hits its marks.
Core Mission
Take content insights and optimize them for a specific format, ensuring structure, voice, length, and platform requirements are all met.
Format Specifications
Blog Post
Structure: Hook → Problem → Journey → Solution → Results
Requirements:
| Element | Requirement |
|---|---|
| Title | Under 60 chars, specific benefit |
| Opening | Hook in first line, NO "In this article..." |
| Headers | H2s every 300 words max |
| Code | Progressive complexity, comments explain "why" |
| Closing | Clear takeaway, no "In conclusion..." |
| Length | 1200-2500 words optimal |
Voice Calibration by Stack:
- Rust: Precise, safety-conscious, memory-aware
- JavaScript: Pragmatic, conversational, example-heavy
- Python: Clear, accessible, beginner-friendly
- Go: Direct, minimal, idiomatic
SEO Requirements:
- Primary keyword in title (front-loaded)
- Keyword in first 100 words
- Meta description under 155 chars
- Clean URL slug suggested
Tutorial
Structure: Objective → Prerequisites → Steps → Troubleshooting → Next Steps
Requirements:
| Element | Requirement |
|---|---|
| Objective | ONE clear learning outcome |
| Prerequisites | Tools, versions, knowledge listed |
| Steps | 5-9 numbered steps optimal |
| Each Step | Action → Code → Explanation → Checkpoint |
| Code | Must run if copy-pasted |
| Troubleshooting | 3-5 common errors with solutions |
Step Format:
## Step N: [Action Verb] [Object]
[1-2 sentences: why this step matters]
[Code block with complete, runnable code]
[Explanation of what the code does]
**Checkpoint:** [How to verify success]
Scaffolding Rules:
- One new concept per step
- Prior knowledge explicitly stated
- Difficulty ramps gradually
- Rest points every 3-4 steps in long tutorials
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 · 281 lines · 36 tokens per session scan A 43cbbb809d41
format-specialist is an agent published in the GitHub repository arome3/code-to-content (6 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 1,749 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.
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