blog

A command that generates a technical blog post from a software project by analyzing its code, dependencies, architecture, history, and development clues.

In plain words
What is it for?
Use it to create a blog post about a codebase, uncover useful technical stories in project files and history, and shape the result around a thesis, opinion, or lesson learned.
Why use it?
It turns project material into a draft while encouraging a clear point of view and checking that the result sounds specific rather than generic. It can proceed from code alone if no extra personal material is provided.

Command for Claude Code

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 commands/arome3/code-to-content/blog
Clone the repo
git clone --depth 1 https://github.com/arome3/code-to-content

Made for: Claude Code.

Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 586 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00009 $0.00586
Opus 5 $0.00005 $0.00293
Sonnet 5 $0.00002 $0.00117
Haiku 4.5 $0.00001 $0.00059

Measured 2d ago against content hash f4800dc70e3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

blog 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.

.claude/commands/c2c/blog.md · 54 lines

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 Blog Post

Generate a compelling technical blog post 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 from references/differentiation.md.

Process

  1. Analyze the Project Analyze the codebase Claude-natively (read dependency files, detect architecture, grep story hooks like TODO/FIXME, mine git log) — see references/analysis-prompts.md. No scripts required.

  2. Load Skill Context Read these files for guidance:

    • skills/code-to-content/SKILL.md (main skill instructions)
    • skills/code-to-content/references/differentiation.md (WHY / opinion / roads-not-taken)
    • skills/code-to-content/references/formats.md (blog section)
    • skills/code-to-content/references/project-analysis.md
    • skills/code-to-content/assets/templates/blog_post.md
  3. Determine Audience Ask the user: Who is this blog post for? (beginners, peers, hiring managers, general developers)

  4. Identify the "Aha Moment" From the analysis, find the single most compelling insight worth sharing:

    • Surprising technical decision
    • Performance improvement with metrics
    • Problem-solving journey
    • Architectural pivot
  5. Generate Content Follow the blog post template structure:

    • Hook that creates immediate curiosity (no "In this article...")
    • Problem → Journey → Solution → Results arc
    • Ground all examples in actual code from the project
    • Extract before/after examples from git history if available
    • Apply voice calibration based on tech stack

Read the full file on GitHub · 54 lines

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. 2d ago First seen · 54 lines · 9 tokens per session scan A f4800dc70e3b

Subscribe to this mod's changes

blog is a command published in the GitHub repository arome3/code-to-content (6 stars, last pushed 2mo ago), licensed MIT. It adds 9 tokens to every session and 586 once invoked, about $0.0000 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.