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.
git clone --depth 1 https://github.com/arome3/code-to-contentWrote 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/commands/arome3/code-to-content/tutorial)<a href="https://agentmods.dev/commands/arome3/code-to-content/tutorial"><img src="https://agentmods.dev/badge/commands/arome3/code-to-content/tutorial/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/arome3/code-to-content/tutorial"><img src="https://agentmods.dev/badge/commands/arome3/code-to-content/tutorial.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00010 | $0.00573 |
| Opus 5.5 | $0.00004 | $0.00229 |
| Sonnet 5.5 | $0.00002 | $0.00115 |
| Haiku 4.5 | $0.00001 | $0.00057 |
Grade A, and why
tutorial 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 1mo 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Technical Tutorial
Create a step-by-step tutorial that teaches developers how to use or build something from the provided project.
Differentiation Discovery (offer; never blocking): Before generating, offer to make this unmistakably theirs — ask for the WHY (the thesis/stakes), one defensible opinion, a road not taken, or a rough draft to polish ("write it ugly; I'll keep your voice"). Rank raw material (Slack threads, support tickets, a voice-memo transcript) above clean specs. If declined, proceed on code alone and flag
Distinctiveness: AT RISK. At delivery, run the swap-the-name test + AI-tells blocklist fromreferences/differentiation.md.
Process
-
Analyze the Project Analyze the codebase Claude-natively (read dependency files, detect architecture, grep story hooks like TODO/FIXME, mine
git log) — seereferences/analysis-prompts.md. No scripts required. -
Load Skill Context Read these files:
skills/code-to-content/SKILL.mdskills/code-to-content/references/differentiation.md(WHY / opinion / roads-not-taken)skills/code-to-content/references/formats.md(tutorials section)skills/code-to-content/assets/templates/tutorial.md
-
Identify Learning Objective Ask the user: What single skill should readers gain from this tutorial?
-
Structure the Tutorial Follow the 6-section structure:
- Hook & Outcome (what they'll build)
- Prerequisites (required knowledge, tools, time)
- Foundation (first 5 minutes - get something working)
- Build (one concept per section)
- Polish (error handling, production considerations)
- Next Steps (extensions, related topics)
-
Apply Progressive Disclosure
- Start with simplest working version
- Add complexity incrementally
- 5-9 numbered steps (one action per step)
- Checkpoint after each step
- Troubleshooting blocks for common errors
-
Validate Ensure content matches audience level using: Estimate readability Claude-natively against the audience thresholds in
references/readability-guide.md(grade level, jargon %, code:prose ratio).
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.
- 1mo ago First seen · 54 lines · 10 tokens per session scan A e2239986daf7
tutorial is a command published in the GitHub repository arome3/code-to-content (7 stars, last pushed 4mo ago), licensed MIT. It adds 10 tokens to every session and 573 once invoked, about $0.0000 per session on Opus 5.5. 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.
Other commands, from other repositories
cn-campus-offer
A workflow for planning a Chinese university recruitment season, building a Chinese and English CV, and practising technical interviews. Campus recruitment is the process of applying to employers through university-focused hiring rounds.
openehr-explain
One-stop router that explains or looks up any openEHR thing — auto-detects an archetype, a template, an RM/AM/BASE type, an RM structural concept, an ADL idiom, an AQL query or keyword, or a terminology code (replaces /archetype-explain, /template-explain, /type-spec, /rm-structure, /adl-idiom, /terminology).
analyze-java
A command for examining an older Java Spring Boot project and creating learning documents about it. Spring Boot is a Java framework commonly used to build web applications and services.
promote
The promote loop — scan your transcripts for what you keep asking, pick a pattern, draft the skill, test its triggers, publish the release package.
rescue-an-account
Workflow recipe — diagnose an at-risk customer and build the full save play through to renewal by chaining 4 skills.
explain
Explain a code file, function, or concept in clear, structured language.