Gr Backlinks

⚠️ 2C 产品的外链调整

本 skill 的 5 类渠道（Wikipedia / 媒体 PR / G2 评测 / Reddit-Quora / HARO）偏 dev/B2B。2C 消费品 / 教育 的权威链接来源不同：

• 教育：学校 / 留学机构 / 考试论坛 / 教育媒体 > 普通付费外链。
• 通用 2C：行业垂直媒体、地区 KOL、社区高赞帖。
• G2 / Capterra（B2B 软件评测站）对 2C 基本无效 → 换 App Store 评分 + 垂类榜单 + 应用媒体测评。
• YMYL 品类：权威机构背书的链接权重远高于数量；切勿买链/造评（Google 数天内识别）。

完整 2C 渠道数据库 + 公开来源见 → gingiris-seo-geo/references/2c-adaptation.md

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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.

Iris now runs two independent domains: gingiris.tools (content/blog, Vercel) and analook.com (product). Both are young domains with near-zero backlink profiles — gingiris.tools restarted from scratch after the 2026-05-27 migration off the banned GitHub Pages account (old github.io link equity is permanently lost, unrecoverable), and analook.com's only inbound links so far are low-DA directory submissions. On-page work alone cannot beat Wikipedia / Hootsuite / Wired for head terms on either domain — only backlink quality + count can. The upside of independent domains: every earned link now accrues to an asset we control, not to a github.io subpath.

Before planning any backlink work, read data/backlinks-status.md first — it records what's already been spent/submitted (directory batches, refunds, pending claims) so we don't re-buy or re-submit.

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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.

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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

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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

Correct sequence

1. Build the case file first (4-12 weeks)

   • Earn 5+ independent press articles via Channels 2 + 3 below
   • Document them in a data/wikipedia-prep/ folder
   • Format: {publication, date, url, key_quote, indepth_or_passing}

2. Wikidata first, Wikipedia second

   • Create a Wikidata entity (much lower notability bar) → builds a structured record AI crawlers find
   • LLMs heavily weight Wikidata for entity recognition

3. Use Articles for Creation (AfC)

   • Submit at https://en.wikipedia.org/wiki/Wikipedia:Articles_for_creation
   • Free, peer-reviewed, 2-8 week wait
   • Pass rate: ~40% if notability is clearly demonstrated

4. Hire a real editor (optional)

   • Search Upwork for "Wikipedia editor 1000+ edits 5+ years"
   • Rate: $80-200/hr
   • Must disclose payment per WP:PAID — non-negotiable
   • Avoid agencies charging fixed $2k+ for "guaranteed" articles (banned by 2026 standards)

Checklist before submission

• Subject has 5+ deep independent sources (not press releases)
• Each notability claim has a citation
• Neutral point of view (no marketing language)
• Wikidata entity exists
• All paid contributors disclosed
• Article has 600-1,500 words (too short = "stub" rejection)

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Channel 2: PR / Authoritative Media

Two paths to backlinks

Path A: Inbound — HARO / Featured.com / Connectively / Qwoted

Journalists request expert quotes daily. Reply with concise, citable answers → published article with backlink.

⚠️ Step 0 — 渠道存活验证（先做，再排周任务）：HARO 品牌 2024-25 经历多轮重组（Connectively 一度关停后 2025-04 重开；HARO 品牌 2025-05 被 Featured.com 收购），"HARO" 老地址/老流程随时可能失效。排任何周任务前，先逐个验证：平台还活着吗？能注册吗？注册后真的收到 query 邮件了吗？ 教训：2026-05-26 审计发现周提醒任务空跑数周——0 个订阅存在，funnel 是空的（memory project_haro_backlinks.md）。当前状态见 data/backlinks-status.md。

• Connectively: connectively.us — 2025-04 重开，AI-spam 较多但可用（Iris expert profile 已建）
• Qwoted: qwoted.com — verification-based，质量最高（Iris source profile 已建）
• Featured.com: featured.com — 2025-05 收购 HARO 品牌，量最大（可选补充）
• 免费补充：Source of Sources (sourceofsources.com) / Help a B2B Writer

验证通过且 query 邮件真的进 inbox 之后，才把该平台排进 weekly cadence。

Reply template (works ~15-25% of the time):

Hi [Journalist],

I'm Iris Wei, ex-COO of AFFiNE (60k+ GitHub stars). For your question
about [topic], here's a 3-sentence answer with concrete data:

[ANSWER: lead with a number, give the mechanism, end with a takeaway.
50-100 words. Cite a specific personal experience, not generic advice.]

If you need a longer quote or follow-up, happy to share more.

— Iris
Site: https://gingiris.tools
Twitter: @WeiYipei

[Disclosure: I run gingiris.tools — no expectation of a link, just a useful quote.]

Pace: 3-5 responses/week. Time/response: 8-12 min. Expected: 1-2 links/month.

Path B: Outbound — Targeted journalist outreach

For deep-dive features, not 1-line quotes.

1. Identify 10 journalists who cover your niche (use Twitter / Muck Rack)
2. Build 3-week warm-up (read + comment on their posts, no DM yet)
3. Pitch a specific story angle (not "want to feature my product")
4. Offer exclusive data, customer interview, or unique angle

Best pitch types for Iris:

• "I led AFFiNE from 0 → 60k GitHub stars. Here's the playbook." (TechCrunch / The Information)
• "Why most OSS marketing playbooks are wrong" (Wired / The Verge)
• "Real data: 30 Product Hunt #1 launches in 4 years" (Fast Company / Forbes)

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Channel 3: Industry Reviews (G2 / Capterra / Product Hunt / SourceForge)

One-time submissions (high ROI for any SaaS / open source)

Platform	URL	What to submit	Backlink type
G2	g2.com/products/new	Product + features	Profile + reviews
Capterra	capterra.com/vendors/sign-up	Product + pricing	Profile + reviews
Product Hunt	producthunt.com/posts/new	Each major version	Listing
SourceForge	sourceforge.net/projects/add	Open source only	Project page
AlternativeTo	alternativeto.net	Free	Profile + alt-listing
StackShare	stackshare.io	Tech stack	Profile

Once submitted, ask early users for genuine reviews (5-10 reviews unlocks featured placement on most platforms).

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Channel 4: Reddit / Quora / Hacker News

Anti-pattern (gets you banned)

• Drop your URL in a top-level post
• Generic "check out my tool" comments
• Multiple accounts (sockpuppeting)

What actually works (builds trust + backlinks naturally)

Reddit:

1. Build account karma to 500+ over 4-8 weeks (comment in non-promotional subs first)
2. Find 5-7 subreddits where your audience hangs out
3. Answer questions deeply with real experience — link to your blog only if it directly answers (1 in 10 responses)
4. Once respected: AMA in r/SaaS, r/Entrepreneur, r/IndieHackers, r/OpenSource

Quora:

1. Pick 3 topics where you can speak with authority
2. Answer specific questions, not topic-wide overviews
3. Each answer: 200-500 words + 1 personal anecdote
4. Link to blog only when blog has the deeper version of your answer

Hacker News:

1. Build karma to 50+ before posting
2. Show HN: best slot Tuesday 9am ET (see existing /gr-oss-marketing for details)
3. Engage with every comment in first 6 hours

Why this matters for GEO

LLMs heavily weight Reddit / Quora content during training:

• ChatGPT cites Reddit ~12% of its responses (2026 Q1 audit)
• Perplexity grounds 18% of answers in Reddit/Quora
• Claude weights Quora answers for "how to" queries

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Channel 5: Generic Backlinks (skip until Channels 1-4 maxed)

Directories, guest posts on low-DA sites, blogger network exchanges. Low GEO value in 2026.

Don't waste time here until Channels 1-4 are mature.

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Workflow: First 30 days for Iris

前置读入：data/backlinks-status.md（已花的钱、已铺的目录、待领的资产——避免重复购买/提交）。

Week 1

• 渠道存活验证（Channel 2A Step 0）+ 补齐缺的平台注册
• Create 1 Featured.com answer per day = 7 responses
• Submit AFFiNE + Gingiris to G2, Capterra, AlternativeTo, StackShare (Channel 3)

Week 2

• HARO/Featured: 5 responses
• Identify 10 journalists covering OSS / SaaS growth (Channel 2B prep)
• Start Reddit karma build in r/SaaS, r/Entrepreneur (Channel 4)

Week 3

• HARO/Featured: 5 responses
• Pitch 3 journalists with specific story angle (Channel 2B)
• Quora: answer 3 questions in your domain

Week 4 + Monthly retro

• HARO/Featured: 5 responses
• Count backlinks earned (use scripts/backlinks-audit.py — Tier 0 free)
• Update Wikipedia case file (Channel 1 prep)

Months 2-3

• First Wikidata entity submission
• First AfC Wikipedia submission (if 5+ independent sources accumulated)
• Reddit AMA in 1 high-fit sub

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Scripts

scripts/backlinks-audit.py (Tier 0 — free, no API)

Uses Common Crawl + verification crawler to get baseline:

• Inbound link count from common crawl
• Verify each known link (HTTP 200 + still links to us)
• Domain-level metrics: in-degree, PageRank approximation, harmonic centrality

Run monthly to track growth.

scripts/haro-helper.py (planned)

• Parse incoming HARO emails
• Auto-suggest which to respond to (based on Iris credentials)
• Draft 3-sentence answer skeletons

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Tracking

Maintain data/backlinks.jsonl (one line per backlink):

{"date":"2026-05-15","from":"techcrunch.com","to":"gingiris.tools","anchor":"AFFiNE","channel":"PR","tier":1,"context":"60k stars article"}

Use this for:

• Monthly retro (Channel mix vs target)
• Phase 2 checkpoint (correlate backlink growth with SERP rank changes)
• Wikipedia case file building

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Anti-patterns (avoid)

• ❌ Paid agency Wikipedia services — sockpuppet farms, articles deleted
• ❌ Reddit coordinated fake accounts — gets you banned permanently
• ❌ Generic HARO replies — quote rate <2% without specific credentials
• ❌ Buying links — Google's algorithm now flags within days
• ❌ Asking friends to write inauthentic reviews on G2 — flagged + removed
• ❌ Guest posting on link farms — negative SEO

Ecosystem links and experiment log

• Prefer legitimate ecosystem placement: relevant Awesome Lists, integration partner pages, package registries, template galleries, conference resources, and README “works with” sections.
• Earn the link with a working integration, useful example, benchmark, or original dataset; follow each repository/site's contribution policy.
• Log date, hypothesis, source, destination, asset, outreach, status, referral visits, activated users, 30d outcome. A live link without relevant visits or activation is not automatically a win.
• Never disguise sponsored placement as editorial coverage; retain disclosure and evidence for every paid or reciprocal placement.

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Cascade recommendations

• Channel 2 PR success → gr-blog-post reference that media article in our content (build social proof)
• Channel 4 Reddit AMA → schedule via gr-oss-marketing
• Wikipedia entity created → update gr-geo-cite to track Wikipedia citations in AI responses (highest-priority test)
• Backlinks accumulated → re-run gr-seo-patrol to measure rank impact

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API dependencies

Service	Env var	Tier	Cost
Common Crawl (CDX index)	none	0 (always)	Free
Moz API	MOZ_TOKEN	1 (optional)	$99/mo
Bing Webmaster API	OAuth	2 (optional)	Free with verified site
DataForSEO Backlinks	DATAFORSEO_B64 (existing)	3 (you have)	Pay per query

Start at Tier 0 + Tier 3 (DataForSEO already configured for gr-seo-patrol).