SEO Machine is a Claude Code workspace for researching, writing, analyzing, and improving long-form search-optimized business content. It is intended for marketers and content teams that need structured workflows for articles, landing pages, keyword research, conversion optimization, and performance analysis. Its catalogued skills, commands, and agents provide the workspace’s content and SEO workflow.
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 commands/thecraighewitt/seomachine/writegit clone --depth 1 https://github.com/TheCraigHewitt/seomachineWrote 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/thecraighewitt/seomachine/write)<a href="https://agentmods.dev/commands/thecraighewitt/seomachine/write"><img src="https://agentmods.dev/badge/commands/thecraighewitt/seomachine/write.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 | $0.00000 | $0.03983 |
| Opus 5 | $0.00000 | $0.01992 |
| Sonnet 5 | $0.00000 | $0.00797 |
| Haiku 4.5 | $0.00000 | $0.00398 |
Grade A, and why
write 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- write — 92% identical, 50 lines differ
How it starts
The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Command
Use this command to create comprehensive, SEO-optimized long-form blog content.
Usage
/write [topic or research brief]
What This Command Does
- Creates complete, well-structured long-form articles (2000-3000+ words)
- Optimizes content for target keywords and SEO best practices
- Maintains your brand voice and messaging throughout
- Integrates internal and external links strategically
- Includes all meta elements for publishing
Process
Pre-Writing Review
- Research Brief: Review research brief from
/researchcommand if available - Brand Voice: Check @context/brand-voice.md for tone and messaging
- Writing Examples: Study @context/writing-examples.md for style consistency
- Style Guide: Follow formatting rules from @context/style-guide.md
- SEO Guidelines: Apply requirements from @context/seo-guidelines.md
- Target Keywords: Integrate keywords from @context/target-keywords.md naturally
Content Structure
1. Headline (H1)
- Include primary keyword naturally
- Create compelling, click-worthy title
- Keep under 60 characters for SERP display
- Promise clear value to reader
2. Introduction (150-250 words)
CRITICAL: Direct Answer First (AI Search Optimization)
For any "best/top/how" query, the first 1-2 sentences MUST directly answer the question. AI scrapers (ChatGPT, Perplexity, Gemini) pull from the top of the page. Don't bury the answer behind narrative.
Example — "best project management tools":
The best project management tools in 2026 are Asana, Monday, and ClickUp — each built for different team sizes and workflows. Here's how they compare.
After the direct answer, use a hook to keep human readers engaged.
Choose ONE hook type for each article:
| Hook Type | Example | Best For |
|---|---|---|
| Provocative Question | "What if the 'free' plan is actually costing you $500/month in lost opportunities?" | Challenging assumptions |
| Specific Scenario | "Last Tuesday, Sarah checked her dashboard and discovered something alarming: her site had been invisible to Google for three weeks." | Creating emotional connection |
| Surprising Statistic | "73% of SaaS users who switch platforms do so within 18 months, and most cite the same three reasons." | Data-driven topics |
| Bold Statement | "Your current tool is lying to you about your numbers." | Controversial takes |
| Counterintuitive Claim | "The cheapest option might be the most expensive decision you make this year." | Comparison content |
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 · 391 lines · 0 tokens per session scan A b99c5247128f
write is a command published in the GitHub repository TheCraigHewitt/seomachine (7,399 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,983 tokens. 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.