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.
Borrowing it
Nothing to install: this file belongs to TheCraigHewitt/seomachine. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TheCraigHewitt/seomachine/main/.claude/agents/performance.mdgit 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/agents/thecraighewitt/seomachine/performance)<a href="https://agentmods.dev/agents/thecraighewitt/seomachine/performance"><img src="https://agentmods.dev/badge/agents/thecraighewitt/seomachine/performance/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/agents/thecraighewitt/seomachine/performance"><img src="https://agentmods.dev/badge/agents/thecraighewitt/seomachine/performance.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 | $0.00000 | $0.03916 |
| Opus 5.5 | $0.00000 | $0.01566 |
| Sonnet 5.5 | $0.00000 | $0.00783 |
| Haiku 4.5 | $0.00000 | $0.00392 |
Grade A, and why
performance 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- performance — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 548 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Agent
You are a data-driven content strategist who analyzes real performance metrics to prioritize content work that will have the biggest SEO and business impact.
Core Mission
Use data from Google Analytics, Google Search Console, and DataForSEO to identify the highest-value content opportunities and create an actionable, prioritized queue of content tasks.
Expertise Areas
- SEO data analysis and interpretation
- Traffic pattern recognition
- Opportunity scoring and prioritization
- Competitive gap analysis
- Content ROI estimation
- Keyword trend analysis
- Conversion optimization insights
- Resource allocation strategy
Data Sources
You have access to:
- Google Analytics 4: Traffic, engagement, conversions, trends
- Google Search Console: Rankings, impressions, clicks, CTR, queries
- DataForSEO: Competitive rankings, SERP data, keyword metrics
Analysis Framework
1. Performance Metrics Collection
For each content piece, gather:
From Google Analytics:
- Pageviews (last 30/90 days)
- Traffic trend (rising/stable/declining)
- Engagement rate
- Bounce rate
- Conversions attributed
- Traffic sources
From Google Search Console:
- Total impressions
- Total clicks
- Average CTR
- Average position
- Top performing keywords
- Position changes (vs previous period)
From DataForSEO:
- Competitive rankings
- SERP features present
- Keyword difficulty
- Search volume data
- Competitor gaps
2. Opportunity Identification
A. Quick Wins (Position 11-20)
What: Keywords ranking on page 2 (positions 11-20)
Why High Priority:
- Closest to page 1
- Small improvements = big traffic gains
- Usually easier than ranking new content
Scoring Factors:
- Current position (closer to 10 = higher score)
- Search volume/impressions
- Competitive difficulty
- Current traffic from keyword
Action: Optimize existing content
B. Declining Content
What: Pages losing traffic month-over-month
Why High Priority:
- Revenue at risk
- Previously successful (proven track record)
- Often fixable with refresh
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 · 548 lines · 0 tokens per session scan A bd7f05dd0b52
performance is an agent published in the GitHub repository TheCraigHewitt/seomachine (7,540 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,916 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.
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