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 MoizIbnYousaf/marketing-cli --skill openseo-competitor-analysisgit clone --depth 1 https://github.com/MoizIbnYousaf/marketing-cliWrote 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/moizibnyousaf/marketing-cli/openseo-competitor-analysis)<a href="https://agentmods.dev/skills/moizibnyousaf/marketing-cli/openseo-competitor-analysis"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/openseo-competitor-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/moizibnyousaf/marketing-cli/openseo-competitor-analysis"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/openseo-competitor-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00125 | $0.01209 |
| Opus 5 | $0.00063 | $0.00605 |
| Sonnet 5 | $0.00025 | $0.00242 |
| Haiku 4.5 | $0.00013 | $0.00121 |
Grade A, and why
openseo-competitor-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 10d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSEO Competitor Analysis
Analyze one competitor deeply enough to decide what to learn from, avoid, counter-position against, or outrank. Findings merge into brand/competitors.md — mktg's competitor memory that competitive-intel maintains qualitatively and this skill now grounds in measured rows.
On Activation
- Catalog + binding:
mktg catalog info openseo --json --fields configured+.seo/openseo.json. No OpenSEO → hand off tocompetitive-intel(Exa qualitative), labeling metricsunknown. - Brand grounding: read
brand/competitors.md+brand/positioning.md(tolerate templates). If the competitor isn't named, ask — never guess the domain.
OpenSEO MCP Tools
get_domain_overview: baseline organic traffic + keyword count (both domains when comparing).get_ranked_keywords: exact keyword/URL/rank/intent/traffic rows. UsemaxRank,minSearchVolume,excludeBrandTerms,resultTypesfilters to keep rows relevant.get_backlinks_overview: backlink/referring-domain profile (may be unavailable — continue without it).find_serp_competitors: validate the named competitor actually overlaps in search.get_serp_results: head-to-head SERP checks for the important shared terms.get_search_console_performance: when comparing to the user's domain and GSC is connected, the USER's baseline is first-party — never estimate your own side from third-party data.research_keywords: expand gap terms.
Workflow
get_domain_overviewfor the competitor (and the user's domain when comparing).get_ranked_keywordsfor the competitor with sensible filters; same for the user, orget_serp_resultsfor shared terms when a lighter check suffices.find_serp_competitorswhen the supplied competitor's search overlap is unclear.- Group keywords into themes: product/category, alternatives/comparisons, templates/tools, educational guides, branded demand.
get_backlinks_overviewwhen authority appears to explain rankings.get_serp_resultsfor the important head-to-head terms.- Synthesize the plan: what they do well, where they're vulnerable, which pages/keywords to pursue, what NOT to copy.
- Merge into
brand/competitors.md(preserve existing sections; date the entry; confirm before overwriting populated competitor entries). - Hand off:
competitor-alternativesfor "X vs Y" pages,seo-contentfor gap-driven briefs,openseo-keyword-clusteringfor page mapping.
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.
- 10d ago First seen · 92 lines · 125 tokens per session scan A 688dd00838c2
openseo-competitor-analysis is a skill published in the GitHub repository MoizIbnYousaf/marketing-cli (31 stars, last pushed 23d ago), licensed MIT. It adds 125 tokens to every session and 1,209 once invoked, about $0.0006 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 2026-08-30.
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