Datasets:

Gingiris
/

gingiris-skills

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
date: timestamp[s]
channel: string
from: string
to: string
action: string
note: string
total_pages: int64
h1_too_long_list: list<item: struct<url: string, len: int64, value: string>>
  child 0, item: struct<url: string, len: int64, value: string>
      child 0, url: string
      child 1, len: int64
      child 2, value: string
summary: struct<title_too_long: int64, h1_too_long: int64, meta_missing: int64, meta_too_short: int64, meta_t (... 145 chars omitted)
  child 0, title_too_long: int64
  child 1, h1_too_long: int64
  child 2, meta_missing: int64
  child 3, meta_too_short: int64
  child 4, meta_too_long: int64
  child 5, canonical_issues: int64
  child 6, slug_stop_words: int64
  child 7, img_alt_issues: int64
  child 8, schema_warns: struct<BlogPosting: int64, Article: int64>
      child 0, BlogPosting: int64
      child 1, Article: int64
slug_stop_words_list: list<item: struct<url: string, detail: string>>
  child 0, item: struct<url: string, detail: string>
      child 0, url: string
      child 1, detail: string
meta_too_short_list: list<item: struct<url: string, len: int64, value: string>>
  child 0, item: struct<url: string, len: int64, value: string>
      child 0, url: string
      child 1, len: int64
      child 2, value: string
title_too_long_list: list<item: struct<url: string, len: int64, value: string>>
  child 0, item: struct<url: string, len: int64, value: string>
      child 0, url: string
      child 1, len: int64
      child 2, value: string
audit_date: timestamp[s]
meta_too_long_list: list<item: struct<url: string, len: int64, value: string>>
  child 0, item: struct<url: string, len: int64, value: string>
      child 0, url: string
      child 1, len: int64
      child 2, value: string
to
{'audit_date': Value('timestamp[s]'), 'total_pages': Value('int64'), 'summary': {'title_too_long': Value('int64'), 'h1_too_long': Value('int64'), 'meta_missing': Value('int64'), 'meta_too_short': Value('int64'), 'meta_too_long': Value('int64'), 'canonical_issues': Value('int64'), 'slug_stop_words': Value('int64'), 'img_alt_issues': Value('int64'), 'schema_warns': {'BlogPosting': Value('int64'), 'Article': Value('int64')}}, 'title_too_long_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'h1_too_long_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'meta_too_short_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'meta_too_long_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'slug_stop_words_list': List({'url': Value('string'), 'detail': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              date: timestamp[s]
              channel: string
              from: string
              to: string
              action: string
              note: string
              total_pages: int64
              h1_too_long_list: list<item: struct<url: string, len: int64, value: string>>
                child 0, item: struct<url: string, len: int64, value: string>
                    child 0, url: string
                    child 1, len: int64
                    child 2, value: string
              summary: struct<title_too_long: int64, h1_too_long: int64, meta_missing: int64, meta_too_short: int64, meta_t (... 145 chars omitted)
                child 0, title_too_long: int64
                child 1, h1_too_long: int64
                child 2, meta_missing: int64
                child 3, meta_too_short: int64
                child 4, meta_too_long: int64
                child 5, canonical_issues: int64
                child 6, slug_stop_words: int64
                child 7, img_alt_issues: int64
                child 8, schema_warns: struct<BlogPosting: int64, Article: int64>
                    child 0, BlogPosting: int64
                    child 1, Article: int64
              slug_stop_words_list: list<item: struct<url: string, detail: string>>
                child 0, item: struct<url: string, detail: string>
                    child 0, url: string
                    child 1, detail: string
              meta_too_short_list: list<item: struct<url: string, len: int64, value: string>>
                child 0, item: struct<url: string, len: int64, value: string>
                    child 0, url: string
                    child 1, len: int64
                    child 2, value: string
              title_too_long_list: list<item: struct<url: string, len: int64, value: string>>
                child 0, item: struct<url: string, len: int64, value: string>
                    child 0, url: string
                    child 1, len: int64
                    child 2, value: string
              audit_date: timestamp[s]
              meta_too_long_list: list<item: struct<url: string, len: int64, value: string>>
                child 0, item: struct<url: string, len: int64, value: string>
                    child 0, url: string
                    child 1, len: int64
                    child 2, value: string
              to
              {'audit_date': Value('timestamp[s]'), 'total_pages': Value('int64'), 'summary': {'title_too_long': Value('int64'), 'h1_too_long': Value('int64'), 'meta_missing': Value('int64'), 'meta_too_short': Value('int64'), 'meta_too_long': Value('int64'), 'canonical_issues': Value('int64'), 'slug_stop_words': Value('int64'), 'img_alt_issues': Value('int64'), 'schema_warns': {'BlogPosting': Value('int64'), 'Article': Value('int64')}}, 'title_too_long_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'h1_too_long_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'meta_too_short_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'meta_too_long_list': List({'url': Value('string'), 'len': Value('int64'), 'value': Value('string')}), 'slug_stop_words_list': List({'url': Value('string'), 'detail': Value('string')})}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

gingiris-skills

Iris / Gingiris 的出海增长工具箱 —— 把 6 个 gingiris-* playbook repo + 每日运营脚本 + 60 篇博客实战经验，打包成 Claude Code skills。

作者：Iris · Gingiris 博客

所有内容开放，可以整套装，也可以只拿一部分。Skill、知识包、原子库、单个脚本都能单独用。

工具箱（v0.4.0 — 12 个 skill）

Skill	做什么
`/gr`	主入口，根据你的问题自动路由
`/gr-seo-patrol`	每日 SEO/GEO 巡逻 — SERP 追踪、canonical 修复、社媒雪崩救援
`/gr-blog-post`	Jekyll 博客发布 — Iris 文风 + hreflang 中英日韩 + FAQ Schema
`/gr-ph-launch`	Product Hunt 发布剧本 — 30x 日冠经验
`/gr-oss-marketing`	开源项目整合营销 — GitHub star、KOL、Reddit/HN/Discord
`/gr-b2b-growth`	B2B SaaS 增长 — PMF → $10M ARR，PLG/SLG 选型
`/gr-aso`	ASO + App 冷启动 — metadata、UGC 矩阵、TikTok 投流
`/gr-user-interview`	用户访谈 — HeyGen 937 访谈方法论
`/gr-competitor`	竞品扫描 — 底层调 actionbook，10x 快，30 tab 并发
`/gr-social-distill`	博客 → 4 社媒变体（X / 小红书 / LinkedIn / dev.to-Zenn），激活 Organic Social
`/gr-geo-cite`	GEO 引用追踪 — 每周跑 4 大 AI 查 gingiris 引用率 + llms.txt v2 自动生成

| /gr-backlinks | 系统化外链建设 — Wikipedia / PR-HARO / G2 / Reddit-Quora 5 通道，0→1 站点 GEO + SEO 共升 |

Roadmap（0.3+）

Skill	来源
`/gr-ph-comment`	包装 `Gingiris/ph-comment-generator`
`/gr-gh-outreach`	包装 `Gingiris/github-issue-generator`
`/gr-readme`	包装 `Gingiris/github-readme-generator`
`/gr-hunter-radar`	结合 actionbook 扫 PH hunter 活跃度

工作流

gr-competitor（看对手在做啥）
    ↓
gr-ph-launch / gr-oss-marketing / gr-b2b（选打法）
    ↓
gr-blog-post（产内容）
    ↓
gr-seo-patrol（上线后监控）
    ↓ cannibalization           ↓ 雪崩
gr-seo-patrol canonical-fix   gr-seo-patrol rescue
    ↓
gr-user-interview（用户反馈）

Skill 之间会自动推荐下一步。比如：

gr-ph-launch 发布 24h 后 → 推荐 gr-seo-patrol 加监控
gr-seo-patrol 发现 cannibalization → 自动跳到 canonical 修复流程
gr-blog-post 发布后 → 自动加入 gr-seo-patrol 监控名单

安装

推荐：Claude Code 插件市场

claude plugin marketplace add Gingiris/gingiris-skills
claude plugin install gr@gingiris-skills

装完在 Claude Code 里输入 /gr 即可。

单独装某个 skill：

claude plugin install gr-seo-patrol@gingiris-skills

知识库

所有方法论文档与原子知识点都开放，即使不装 skill 也能用。

目录结构

知识库/
├── 原子库/
│   ├── atoms.jsonl                    # 结构化知识原子（可 RAG）
│   └── README.md
└── Skill知识包/
    ├── iris_writing_style.md          # 文风指南（5 要素）
    └── seo_geo_playbook_2026.md       # SEO 飞轮 + GEO 三件套

怎么在你自己的项目里用

场景 1：给你的 AI 加 SEO 诊断能力 把 知识库/Skill知识包/seo_geo_playbook_2026.md 粘到 system prompt。

场景 2：做 RAG atoms.jsonl 导向量库，每条带 topics 标签。

场景 3：只要脚本 skills/gr-seo-patrol/scripts/*.py 可独立跑，看 docs/api-keys-template.md 配 env。

API 依赖

见 docs/api-keys-template.md。

核心：DATAFORSEO_B64 + GITHUB_TOKEN，其他 skill 按需加。

许可证

MIT。

个人使用、学习、研究：随便
商业用途：随便
衍生作品：建议（不强制）注明来源

Monthly Full-Site Audit Workflow

Battle-tested 2026-05-07 on a 58-page blog. Caught 43 SERP-truncating titles + 36 schema warns + 27 stop-word slugs in a single 30-min run. One layout-level commit fixed 20 of 43 titles. Use for any Jekyll / Hugo / Next.js blog with 30+ posts.

A repeatable 6-stage workflow you can run on any site. Powered by 4 scripts (see attribution below).

Stage 1 — Discovery (5 min)

Pull all blog URLs from your sitemap:

import urllib.request, re
sm = urllib.request.urlopen("https://your-site.com/sitemap.xml").read().decode()
urls = [u for u in re.findall(r"<loc>([^<]+)</loc>", sm) if "/blog/" in u]

Stage 2 — Parallel Audit (20 min for 60 pages)

Run two audit scripts per URL in 4-thread parallel:

pip install requests
python3 skills/gr-seo-patrol/scripts/check-page.py URL --timeout 20
python3 skills/gr-seo-patrol/scripts/check-schema.py URL --timeout 20

Each script outputs a structured JSON envelope (status: pass|warn|fail|info per check).

Stage 3 — Aggregate Findings

Bucket issues by type:

Title length > 70 chars (SERP truncation risk)
H1 length > 70 chars (mobile readability)
Meta description outside 80-170 chars
Schema warns by @type (BlogPosting / Article / Organization)
Canonical mismatches, slug stop words, missing alt text

Save aggregated counts + per-URL lists to findings.json.

Stage 4 — Layered Fix Strategy (HIGH ROI ORDER)

Order	Layer	Scope	Typical commits	ROI
1️⃣	Layout (`_layouts/default.html`)	Schema bugs, title suffix, dateModified injection	1	🔥 fixes 20+ pages at once
2️⃣	Config (`_config.yml`)	Logo URL, twitter, social, author structure	1	fixes site-wide
3️⃣	Per-article batch	Trim long titles/H1s, expand short meta	10-20	per-file, parallelizable
4️⃣	Skip	Slug stop words (changing breaks 301), low-traffic old articles	0	low ROI

Stage 5 — Verify

After Jekyll/Hugo rebuild (~60-90s), re-run check-schema.py on a sample page. All schema types should show status: pass: Article · BlogPosting · Organization · FAQPage

Stage 6 — Archive + Trend Track

Commit findings.json to data/audit-{YYYY-MM-DD}.json for month-over-month trend analysis. Add 2-5 atoms to 知识库/原子库/atoms.jsonl documenting any new lessons.

Schedule it

Add a monthly cron to auto-run before your Phase 2 / quarterly checkpoint:

# In Claude Code's scheduled-tasks
cronExpression: "0 10 1 * *"   # 10am on day 1 of each month
prompt: "Run Monthly Full-Site Audit per gr-seo-patrol/SKILL.md workflow..."

What you'll typically find on your first run

Real numbers from gingiris.github.io/growth-tools 2026-05-07 run:

Issue	Count	Resolution path
Title >70 chars	43/58	Layout-level (-20 chars suffix) + 13 per-article retrim
Schema warns	36	Layout-level (dateModified + publisher.logo + contactPoint)
H1 >70 chars	23	Per-article trim (paired with title)
Meta too short/long	20	Per-article (i18n posts often hit this)
Slug stop words	27	SKIP (would break 301 redirects)
HTTP errors	2	Investigate (likely deleted/renamed)

Total time: ~30 min audit + 90 min fixes = 2 hours for site-wide SEO health refresh.

HARD RULE (anti-hallucination guardrail)

⛔ Output ONLY the checks defined in the script's JSON envelope.

Do NOT add "bonus" checks not in the script output
Do NOT contradict the script's status field without observable evidence
Do NOT invent metrics like "EEAT score 89" — third-party scoring is unofficial per Google 2026 guidance
If llm_review_required: true, make explicit judgment + document reasoning + update status

The script envelope is the single source of truth. Treat as strict whitelist.

Script attribution

The 4 audit scripts (check-page.py, check-schema.py, check-site.py, check-social.py) in skills/gr-seo-patrol/scripts/ are adapted from JeffLi1993/seo-audit-skill (MIT). Original repo focused on single-page client-presentable HTML reports; we adapted them for orchestrated batch audit + Jekyll/GitHub Pages site analysis. Original license terms preserved in each file header.

关联 repo

Gingiris/growth-tools — 主 blog，所有 skill 的实战场
Gingiris/gingiris-launch — PH launch playbook 内容源
Gingiris/awesome-agent-skills — skills 生态索引
dontbesilent2025/dbskill — 框架灵感来源
JeffLi1993/seo-audit-skill — 单页 SEO 审计脚本来源（4 scripts adapted）
AgriciDaniel/claude-seo — 25-skill SEO 全套（含外链分析，可作 Tier 3 扩展）
zubair-trabzada/geo-seo-claude — GEO 0-100 评分体系（可作 gr-geo-cite 增强）

贡献

发 Issue 描述你的运营场景
PR 加新 skill / 新原子 / 新方法论
跟 @WeiYipei 聊

关于作者 / About the Author

Iris（生姜iris） — AFFiNE 联合创始人兼 COO（融资 $10M，60k+ GitHub Stars）。Forbes 亚洲 30 Under 30。辅导 150+ AI 创业公司完成全球 GTM、SEO/GEO、Product Hunt 发布、B2B 增长。

Former cofounder & COO of AFFiNE ($10M raised, 60k+ GitHub stars). Forbes Asia 30 Under 30. Coached 150+ AI startups on global GTM, SEO/GEO, Product Hunt launches, and B2B growth.

网站 / Website: gingiris.com
Twitter/X: @WeiYipei
Telegram: @Iris_carrot
Blog: gingiris.github.io/growth-tools

🗂️ See Also — Gingiris Playbook Series on HuggingFace

Playbook	Focus	HuggingFace
gingiris-growth-finder	🧭 Meta-router: diagnoses your situation, picks the right playbook	Gingiris/gingiris-growth-finder
gingiris-launch	🚀 Product Hunt launch, KOL outreach, UGC growth	Gingiris/gingiris-launch
gingiris-opensource	⭐ GitHub stars, HN, OSS go-to-market	Gingiris/gingiris-opensource
gingiris-b2b-growth	📈 B2B SaaS PLG/SLG, PMF to $10M ARR	Gingiris/gingiris-b2b-growth
gingiris-aso-growth	📱 ASO, mobile cold start, UGC matrix	Gingiris/gingiris-aso-growth
gingiris-seo-geo	🔍 SEO + GEO dual-engine, AI search citations	Gingiris/gingiris-seo-geo
gingiris-user-interview	🎤 User interview framework (HeyGen 937 methodology)	Gingiris/gingiris-user-interview
growth-tools	📚 Blog & tools hub	Gingiris/growth-tools

All playbooks live at gingiris.com and skills.sh/Gingiris.

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