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 skills add amirjahfar1/automate-seo-with-claude --skill seo-competitor-gap-analysisgit clone --depth 1 https://github.com/amirjahfar1/automate-seo-with-claudeWrote 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/skills/amirjahfar1/automate-seo-with-claude/seo-competitor-gap-analysis)<a href="https://agentmods.dev/skills/amirjahfar1/automate-seo-with-claude/seo-competitor-gap-analysis"><img src="https://agentmods.dev/badge/skills/amirjahfar1/automate-seo-with-claude/seo-competitor-gap-analysis/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/skills/amirjahfar1/automate-seo-with-claude/seo-competitor-gap-analysis"><img src="https://agentmods.dev/badge/skills/amirjahfar1/automate-seo-with-claude/seo-competitor-gap-analysis.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 | $0.00075 | $0.01613 |
| Opus 5 | $0.00037 | $0.00807 |
| Sonnet 5 | $0.00015 | $0.00323 |
| Haiku 4.5 | $0.00007 | $0.00161 |
Grade A, and why
seo-competitor-gap-analysis 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Example output: examples/seo-competitor-gap-analysis-wix-com-20260514/REPORT.md
Competitor Gap Analysis
Identify the specific keywords your competitors rank for in the top 20 that your domain does not, ranked by commercial value and realistic capture difficulty.
Prerequisites
- DataForSEO MCP server connected.
- User provides: (a) target domain, (b) 3 to 5 competitor domains (or ask the skill to auto-discover them), (c) market country (default:
us), and optionally filters (min volume, max KD, intent).
Process
-
Validate or discover competitors
mcp__dataforseo__dataforseo_labs_google_competitors_domain- If the user did not provide competitors, pull the top 5 organic competitors for the target in the target market.
- Surface the list to the user and ask them to confirm or override before proceeding.
- Note: large competitor lists can exceed the MCP inline limit. Cap with
limitand filters; if the result is written to a file, read that path, parse the{data: [...]}JSON, sort bycommon_keywordsdesc, and take the top 5.
-
Pull competitor keyword sets
mcp__dataforseo__dataforseo_labs_google_ranked_keywords- For each competitor, pull keywords where they rank in the top 20 of the target country.
- Save per-competitor lists.
-
Pull target keyword set
mcp__dataforseo__dataforseo_labs_google_ranked_keywords- For the target domain, pull all ranking keywords in the target country (any position).
- This is the exclusion set.
-
Compute the gap
mcp__dataforseo__dataforseo_labs_google_domain_intersection(cross-check)- Keywords ranked by at least one competitor in the top 20 but not ranked by the target domain at all.
- Use the domain-intersection endpoint as a cross-check.
-
Filter and segment
- Apply user-specified filters on volume, KD, and intent.
- Segment by intent: informational, commercial, transactional, navigational.
- Segment by competition: how many of the N competitors rank for each gap keyword.
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.
- 12d ago First seen · 122 lines · 75 tokens per session scan A 943242eb0b2b
seo-competitor-gap-analysis is a skill published in the GitHub repository amirjahfar1/automate-seo-with-claude (2 stars, last pushed 3mo ago), licensed MIT. It adds 75 tokens to every session and 1,613 once invoked, about $0.0004 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.
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