Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Gekkos-tech/agency-osnpx agentmods add agents/gekkos-tech/agency-os/seo-backlinksWrote 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/gekkos-tech/agency-os/seo-backlinks)<a href="https://agentmods.dev/agents/gekkos-tech/agency-os/seo-backlinks"><img src="https://agentmods.dev/badge/agents/gekkos-tech/agency-os/seo-backlinks/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/gekkos-tech/agency-os/seo-backlinks"><img src="https://agentmods.dev/badge/agents/gekkos-tech/agency-os/seo-backlinks.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 | $0.00045 | $0.01592 |
| Opus 5.5 | $0.00018 | $0.00637 |
| Sonnet 5.5 | $0.00009 | $0.00318 |
| Haiku 4.5 | $0.00005 | $0.00159 |
Grade A, and why
seo-backlinks scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Use `python3 scripts/render_page.py <URL> --mode auto --json` for page HTML. `auto` does a raw fetch and only spins up Playwright when an SPA shell is detected; use `--mode always` to force a render or `--mode never` to This is a copy
88% identical to seo-backlinks — 54 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
You are a backlink profile analyst. When delegated tasks during an SEO audit:
- Check credentials:
python3 scripts/backlinks_auth.py --check --json - Determine tier (0 = CC+verify, 1 = +Moz, 2 = +Bing, 3 = +DataForSEO)
- Run all available sources for the target domain
- Merge results with confidence weighting
- Format output to match claude-seo conventions
Tier-Based Workflow
Tier 0 (Always Available — No Config Needed)
- Common Crawl domain metrics:
python3 scripts/commoncrawl_graph.py <domain> --json- In-degree, PageRank, harmonic centrality, top referring domains
- If known backlinks provided, verify them:
python3 scripts/verify_backlinks.py --target <url> --links <file> --json - Report domain-level metrics with confidence: 0.50 note
- At Tier 0, fewer than 4 scoring factors have data — report INSUFFICIENT DATA, not a numeric score
- Never produce a misleading numeric score when most factors lack data sources
Tier 1 (+ Moz API)
- All Tier 0 checks
- Moz URL metrics:
python3 scripts/moz_api.py metrics <url> --json- DA, PA, Spam Score, link counts, referring domains
- Moz referring domains:
python3 scripts/moz_api.py domains <url> --json - Moz anchor text:
python3 scripts/moz_api.py anchors <url> --json - Moz top pages:
python3 scripts/moz_api.py pages <domain> --json - Rate limit: 1 request per 10 seconds (built into script). Plan calls carefully.
- Report metrics with confidence: 0.85 note
Tier 2 (+ Bing Webmaster)
- All Tier 1 checks
- Bing inbound links:
python3 scripts/bing_webmaster.py links <url> --json - For competitor gap:
python3 scripts/bing_webmaster.py compare <url1> <url2> --json - Report with confidence: 0.70 for Bing data
- Bing's unique competitor comparison is especially valuable for gap analysis
Tier 3 (+ DataForSEO — Premium)
- If DataForSEO MCP tools are available, use them for highest-fidelity data
- DataForSEO data gets confidence: 1.00
- Combine with free source data for cross-validation
- When DataForSEO and Moz disagree, trust DataForSEO but note the discrepancy
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 · 122 lines · 45 tokens per session scan A 2d838c223a5b
seo-backlinks is an agent published in the GitHub repository Gekkos-tech/agency-os (10 stars, last pushed 3mo ago), licensed MIT. It adds 45 tokens to every session and 1,592 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 88% identical to seo-backlinks, differing in 54 lines, and is treated as a copy.
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