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-competitive-landscapegit 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-competitive-landscape)<a href="https://agentmods.dev/skills/moizibnyousaf/marketing-cli/openseo-competitive-landscape"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/openseo-competitive-landscape/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-competitive-landscape"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/openseo-competitive-landscape.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 | $0.00119 | $0.01239 |
| Opus 5 | $0.00060 | $0.00620 |
| Sonnet 5 | $0.00024 | $0.00248 |
| Haiku 4.5 | $0.00012 | $0.00124 |
Grade A, and why
openseo-competitive-landscape 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 today.
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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSEO Competitive Landscape
Answer with measured data: who is winning this SEO market, what content works for them, and where the openings are. Findings update brand/landscape.md (mktg's market memory) with an evidence tier mktg's landscape-scan cannot reach alone.
On Activation
- Readiness + binding:
mktg seo status --json --fields readiness,catalog.endpointError,project.not_configured→ fall back tolandscape-scan(Exa qualitative) and label authority/metricsunknown. For a ready state, verify live access with the freewhoamiMCP tool before paid calls. - Brand grounding: read
brand/landscape.md+brand/competitors.md(tolerate templates) — known competitors seed the query set; positioning filters "SEO competitor" from "business competitor."
OpenSEO MCP Tools
research_keywords+get_keyword_metrics: build + validate a 5–10 query market set (mixed intent: informational, commercial, comparison, tool terms).find_serp_competitors: recurring domains across the keyword set at scale — use before manual SERP counting.get_serp_results: inspect live SERP composition/features (≤10 queries per call).get_domain_overview: organic footprint for top 3–5 recurring domains.get_ranked_keywords: exact ranking keywords/URLs/intents for leaders.get_backlinks_overview: authority comparison where rankings look authority-driven (may be unavailable on some accounts — continue without it).get_backlinks_profile: sampled link-level evidence for leaders when overview totals are too coarse; record scope, filters, and pagination.get_search_console_performance: when the user's own domain is compared and GSC is connected, anchor THEIR side with first-party data instead of third-party estimates.
Workflow
- Define the market query set (positioning-filtered, mixed intent).
find_serp_competitorsfor recurring domains;get_keyword_metricsto validate demand/difficulty.- Group recurring domains by type: direct product competitors, publishers/media, marketplaces/directories, communities/forums, docs/resources.
get_domain_overviewtop 3–5;get_ranked_keywordsfor direct competitors + relevant publishers;get_backlinks_overviewwhere authority explains wins.- Synthesize: winning content types, SERP formats, authority advantages, underserved angles.
- Update
brand/landscape.md: leaders, winnable area, biggest barrier, query set used, content formats that work, keyword/theme gaps — dated, with the measured-vs-estimate caveat. - Recommend next:
openseo-competitor-analysis(one domain),openseo-keyword-clustering(page mapping), orseo-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.
- today Changed · +1 lines 8af7cc049967
- 12d ago First seen · 88 lines · 119 tokens per session scan A d354d780cc2f
openseo-competitive-landscape is a skill published in the GitHub repository MoizIbnYousaf/marketing-cli (31 stars, last pushed today), licensed MIT. It adds 119 tokens to every session and 1,239 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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