A command that turns a technical insight or project into a Twitter/X thread, a sequence of connected short posts. It can inspect a project and look for details that make the thread specific to it.

Use it to draft threads about software projects, technical decisions, or lessons learned from a codebase.

It helps turn development work into a structured public explanation while checking that the result is based on real project material.

twitter — Command by arome3

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/twitter

Clone the repo

git clone --depth 1 https://github.com/arome3/code-to-content

Made for: Claude Code.

Per session 10 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 546 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.

Model	Per session	Once invoked
Fable 5	$0.00010	$0.00546
Opus 5	$0.00005	$0.00273
Sonnet 5	$0.00002	$0.00109
Haiku 4.5	$0.00001	$0.00055

Measured 2d ago against content hash b52c7c90c145, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

twitter 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/twitter.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 Twitter Thread

Create an engaging Twitter/X thread from a technical insight or 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

Understand the Input
- If path provided: Analyze it Claude-natively (read deps, grep story hooks, mine git log; see references/analysis-prompts.md)
- If topic provided: Proceed directly to insight extraction
Load Skill Context Read these files:
- skills/code-to-content/SKILL.md
- skills/code-to-content/references/differentiation.md (WHY / opinion / roads-not-taken)
- skills/code-to-content/references/social-content.md
- skills/code-to-content/assets/templates/twitter_thread.md
Identify Core Insight What's the ONE thing worth sharing? The hook must create curiosity. Good hooks:
- Surprising result or metric
- Contrarian take on common practice
- "I was wrong about X" confession
- Before/after transformation
Generate Thread (8-12 tweets) Structure:
- Tweet 1: HOOK (most important - surprising claim or result)
- Tweets 2-3: Context and problem
- Tweets 4-6: Journey and insight
- Tweets 7-8: Solution and results
- Tweet 9+: Takeaway and CTA
Format Rules
- Each tweet under 280 characters
- Each tweet has standalone value (could be RT'd alone)
- Include visual suggestions (code screenshots, diagrams)
- End with engagement CTA (question, RT request, follow)
Deliver Present thread with:
- Copy-paste ready format (numbered)
- Visual suggestions for each tweet that needs one
- Alternative hook options (2-3)
- Best posting time recommendation

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.

2d ago First seen · 54 lines · 10 tokens per session scan A b52c7c90c145

Subscribe to this mod's changes

twitter is a command published in the GitHub repository arome3/code-to-content (6 stars, last pushed 2mo ago), licensed MIT. It adds 10 tokens to every session and 546 once invoked, about $0.0001 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.

Learning and teaching Writing and docs claude-code claude-plugins claude-skills content-generation dev-rel skills

twitter

Getting it into your agent

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

Generate Twitter Thread

Process

What this file has done since we first saw it

Other commands, from other repositories

retrospective

revise-claude-md

protracted-strategy

resume_handoff

distill

demo-command