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.
git clone --depth 1 https://github.com/XuanRanL/loamwright-SEO-SkillWrote 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/xuanranl/loamwright-seo-skill/audit-backlinks)<a href="https://agentmods.dev/agents/xuanranl/loamwright-seo-skill/audit-backlinks"><img src="https://agentmods.dev/badge/agents/xuanranl/loamwright-seo-skill/audit-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/xuanranl/loamwright-seo-skill/audit-backlinks"><img src="https://agentmods.dev/badge/agents/xuanranl/loamwright-seo-skill/audit-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 | $0.00036 | $0.01077 |
| Opus 5 | $0.00018 | $0.00539 |
| Sonnet 5 | $0.00007 | $0.00215 |
| Haiku 4.5 | $0.00004 | $0.00108 |
Grade A, and why
audit-backlinks 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 9d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Backlinks Agent
Spawn Condition
Always spawns. Common Crawl (tier 0) is free and requires no API key. Higher tiers used when available.
Inputs
{audit_dir}/config.json— domain, optional keys: moz, bing_webmaster, dataforseo{audit_dir}/crawl-results.json— internal link structure for cross-reference
Scripts
(Invocations below are the REAL CLIs — positional args, not --domain/--urls flags. Pinned by tests/test_commoncrawl_graph_cli_and_agent_doc.py, which parses these lines against each module's actual argparse.)
python -m scripts.audit.commoncrawl_graph {domain} --json— free backlink discovery (positional domain; optional--crawl,--max-download-mb,--cache-dir)python -m scripts.audit.verify_backlinks {file} --json— HTTP-verify link existence ({file} = JSON array of{"source_url", "target_url", "anchor_text"}objects; or pipe the array via--stdin)python -m scripts.audit.moz_api {domain} --json— DA/PA + links (if key; positional domain)python -m scripts.monitor.bing_webmaster_ingest --site {site_slug} --json— Bing Webmaster data (if key;--sitetakes the project slug, not a domain)
Read references/audit/backlink-quality.md before analysis.
Confidence Tiers
CC+verify 0.50 | Bing 0.70 | Moz 0.85 | DataForSEO 1.00. Use highest available; report tier in metadata.
Scoring Dimensions
Referring Domain Count (20%) — Benchmark by vertical: local 30-80, SaaS 200-500, e-commerce 100-300, publisher 500-2000. Score 100 at competitor median, linear to 0 at 10% of median.
Domain Quality Distribution (20%) — Tier 1 DA 60+ (news, .edu, .gov): 10-20%. Tier 2 DA 30-59: 30-40%. Tier 3 DA 10-29: 30-40%. Tier 4 DA < 10: < 15%. HIGH if Tier 4 > 30%.
Anchor Text Naturalness (15%) — Branded should dominate (SaaS 40-55%, local 45-60%, e-commerce 35-45%, publisher 30-40%). HIGH if exact-match > 20% (Penguin over-optimization signal).
Toxic Link Ratio (20%) — Toxic patterns: 10K+ outbound links (link farm), exact-match from unrelated domain, PBN footprint, hacked-site spam. Score: < 3% toxic = 100, 3-8% = 75, 8-15% = 50, 15-25% = 25, > 25% = 0. CRITICAL if > 25%.
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.
- 9d ago First seen · 58 lines · 36 tokens per session scan A 978a2ba25eb8
audit-backlinks is an agent published in the GitHub repository XuanRanL/loamwright-SEO-Skill (47 stars, last pushed 22d ago), licensed Apache-2.0. It adds 36 tokens to every session and 1,077 once invoked, about $0.0002 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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