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 Gingiris/gingiris-skills --skill gr-backlinksgit clone --depth 1 https://github.com/Gingiris/gingiris-skillsWrote 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/gingiris/gingiris-skills/gr-backlinks)<a href="https://agentmods.dev/skills/gingiris/gingiris-skills/gr-backlinks"><img src="https://agentmods.dev/badge/skills/gingiris/gingiris-skills/gr-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/skills/gingiris/gingiris-skills/gr-backlinks"><img src="https://agentmods.dev/badge/skills/gingiris/gingiris-skills/gr-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 | $0.00102 | $0.02964 |
| Opus 5.5 | $0.00041 | $0.01186 |
| Sonnet 5.5 | $0.00020 | $0.00593 |
| Haiku 4.5 | $0.00010 | $0.00296 |
Grade A, and why
gr-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 2mo 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 — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gr-backlinks — Systematic Backlink Building
Why this skill exists
Phase 2 missing piece: We do title/content/schema/cluster optimization but have zero systematic backlink work. Article research (2026-05): backlinks are the #1 GEO signal — LLMs decide citations partly by brand authority, which is downstream of backlink graph.
For Iris's site (gingiris.github.io, subpath under GitHub Pages), the domain authority ceiling is fundamentally capped without external backlinks. No on-page work can beat Wikipedia / Hootsuite / Wired for head terms — only backlink quality + count can.
The 5-Channel Priority Matrix
Adopted from 2026-05 WeChat article + JeffLi1993 / AgriciDaniel / zubair-trabzada skills audit:
| Channel | SEO Value | GEO Value | Priority | Effort/week |
|---|---|---|---|---|
| Wikipedia dedicated entry | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ | MAX | 3-6h (one-time setup, ongoing edits) |
| Authoritative media (PR) | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | MAX | 2h (HARO + outreach) |
| Industry reviews (G2/Capterra/PH) | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | HIGH | 1h (one-time submission) |
| Reddit/Quora discussions | ⭐⭐ | ⭐⭐⭐⭐ | HIGH | 2h (sustained presence) |
| Generic backlinks (directories/blogs) | ⭐⭐⭐ | ⭐⭐ | MED | skip until top 3 done |
Rule: Start from highest GEO value. SEO-only signals (DA passing) are less leveraged than 2-3 years ago.
When to use this skill
- "I want to build backlinks for my site"
- "How do I get into Wikipedia?"
- "How do I do HARO / Featured.com?"
- "What's a Reddit / Quora strategy that doesn't get me banned?"
- "How do I get into G2 / Capterra?"
- Phase 2 monthly checkpoint shows domain authority capping ranking
Channel 1: Wikipedia (highest GEO leverage)
Reality check before you start
- Wikipedia is notability-gated, not effort-gated
- Threshold: 5+ independent reliable-source articles discussing your subject substantively (not in passing)
- Listicle mentions, PR releases, sponsored content do NOT count
- Paid Wikipedia services (Fiverr / WikiExperts / Wiki Mavericks): 80% of articles deleted within 6 months — they fail notability not because of editor skill
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- haro-pitch-library.md 2.1 KB
- scripts/backlinks-audit.py 7.2 KB runs code
- submissions/alternativeto-submission.md 1.4 KB
- submissions/capterra-submission.md 1.1 KB
- submissions/g2-submission.md 1.8 KB
- submissions/stackshare-submission.md 1.4 KB
- submissions/wikidata-affine.md 2.4 KB
- templates/haro-response.md 2.8 KB
- templates/reddit-quora.md 4.7 KB
- templates/wikipedia-prep.md 5.5 KB
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.
- 2mo ago First seen · 288 lines · 102 tokens per session scan A 0e5e6974b591
gr-backlinks is a skill published in the GitHub repository Gingiris/gingiris-skills (24 stars, last pushed 5mo ago), licensed MIT. It adds 102 tokens to every session and 2,964 once invoked, about $0.0004 per session on Opus 5.5. 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.
gr-backlinks compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gr-backlinksGingiris/gingiris-skills | Skill | 24 | 5mo ago | MIT | A | 102 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |