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-link-prospectinggit 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-link-prospecting)<a href="https://agentmods.dev/skills/moizibnyousaf/marketing-cli/openseo-link-prospecting"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/openseo-link-prospecting/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-link-prospecting"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/openseo-link-prospecting.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 | $0.00113 | $0.01311 |
| Opus 5 | $0.00056 | $0.00656 |
| Sonnet 5 | $0.00023 | $0.00262 |
| Haiku 4.5 | $0.00011 | $0.00131 |
Grade A, and why
openseo-link-prospecting 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 11d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSEO Link Prospecting
Find pages, sites, and authors that might realistically reference the user's linkable asset — then hand off-page-seo a qualified target list at .seo/backlink-targets.json instead of a cold start.
On Activation
- Catalog + binding:
mktg catalog info openseo --json --fields configured+.seo/openseo.json. No OpenSEO → prospect with Exa search only (queries below still apply) and label authority dataunknown. - Clarify the asset: what page/study/tool/template is being promoted and WHY someone would reference it. No clear asset + reason → fix that first; outreach without a reason is spam.
- Read
brand/positioning.mdfor angle/audience fit (tolerate missing).
OpenSEO MCP Tools
get_serp_results: find ranking articles, listicles, resource pages, comparisons, statistics pages (≤10 queries per call).get_backlinks_overview: competitor backlink/referring-domain patterns — where do THEY get links (may be unavailable; continue without).get_domain_overview: qualify strong prospect domains.get_ranked_keywords: topical-fit checks on prospects/competitors.research_keywords: expand prospecting queries.
Contact Discovery (NOT OpenSEO)
Contact paths come from web/search/browser tools (Firecrawl fetch, Exa search, browser automation) — never attribute these to OpenSEO:
- Author byline pages, contact pages, editorial guidelines, about/team pages
- LinkedIn/X/Bluesky profiles, newsletter mastheads
- Public emails in HTML or visible text;
Person/Organization/sameAs/emailstructured data
Record only contact details actually found, each with its source URL.
Prospecting Query Patterns
<topic> resources · best <category> tools · <competitor> alternatives · <topic> statistics · <topic> guide · <topic> examples · <topic> templates · <topic> software · <topic> for <audience>
Workflow
- Build 5–10 prospecting queries from the asset;
get_serp_resultsin batches. - Competitors supplied?
get_backlinks_overviewtheir strongest domains first. - Filter: keep editorial pages, resource lists, comparisons, statistics, templates, curated directories. Drop homepages, login walls, thin affiliate, spam, and direct competitors (unless a comparison angle is valid).
- Per prospect, define the angle: broken/missing resource, better current data, useful tool/template, comparison inclusion, expert quote.
- Contact discovery on the strongest prospects via web tools (source URLs recorded).
- Write targets to
.seo/backlink-targets.json:
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.
- 11d ago First seen · 102 lines · 113 tokens per session scan A a689a2c4eec1
openseo-link-prospecting is a skill published in the GitHub repository MoizIbnYousaf/marketing-cli (31 stars, last pushed 24d ago), licensed MIT. It adds 113 tokens to every session and 1,311 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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