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
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/article)<a href="https://agentmods.dev/commands/thecraighewitt/seomachine/article"><img src="https://agentmods.dev/badge/commands/thecraighewitt/seomachine/article.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 5.1 | $0.00000 | $0.04477 |
| Opus 5 | $0.00000 | $0.02239 |
| Sonnet 5 | $0.00000 | $0.00895 |
| Haiku 4.5 | $0.00000 | $0.00448 |
Grade A, and why
article 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 6d 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:
- article — 86% identical, 21 lines differ
How it starts
The opening of the file, as written. The whole thing — 623 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Article Command
A unified content creation pipeline that produces comprehensive, SEO-optimized articles through mandatory research, strategic planning, and section-by-section writing.
Usage
/article [topic]
Examples:
/article "Best Project Management Tools for Small Teams"/article "Content Marketing Strategy Guide 2025"/article "How to Migrate from Competitor to Your Product"
What This Command Does
Creates high-quality articles by enforcing a 4-step pipeline where research is mandatory, not optional:
STEP 1: SERP Analysis → See what Google rewards TODAY
STEP 2: Social Research → Mine Reddit + YouTube for real insights
STEP 3: Article Planning → Section-by-section strategy
STEP 4: Section Writing → Write/edit each section individually
This prevents the "AI knows everything" trap that produces generic content matching competitors instead of beating them.
When to Use This vs /write
| Scenario | Command |
|---|---|
| Comprehensive new article | /article |
| Competitive topics | /article |
| Topics where you need to beat existing content | /article |
| Quick drafts from existing research | /write |
| Simple updates to existing content | /write |
STEP 1: SERP Analysis (MANDATORY)
You MUST research before writing. No exceptions.
Process
-
Search the Target Keyword Use WebSearch to find what's currently ranking:
WebSearch: "[topic] industry" OR "[topic] industrying" -
Analyze Top 5 Ranking Articles For each top-ranking article, use WebFetch and document:
Element What to Capture Structure H2 headings, section order, content type Word Count Approximate length Gaps Topics covered superficially (<150 words) Missing Angles Perspectives not addressed Unsupported Claims Statements without data/sources Outdated Info Old statistics, deprecated tools What They Do Well Strong sections to match
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.
- 6d ago First seen · 623 lines · 0 tokens per session scan A c3c330c96914
article is a command published in the GitHub repository TheCraigHewitt/seomachine (7,400 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,477 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
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
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.