Blog 3p Review logo

Blog 3p Review

Organization
flaqai
blog-3p-review

仅在博客 3P 的 WR 独立审稿路线审阅证据、文章和人工交付包;输出有证据的问题项、独立 FULL_REVIEW 或有限 R-Δ。默认 WQ 作者自查不调用本角色。

Overview

Publisherflaqai
Repositorybacklink_skills
Skill nameblog-3p-review
Stars
760
Forks
237
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by flaqai on GitHub. Read the source before you install it.

Installation

Install the Blog 3p Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/flaqai/backlink_skills/tree/main/blog-3p-skill-matrix/skills/blog-3p-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/flaqai/backlink_skills.git /tmp/backlink_skills
mkdir -p .claude/skills
cp -r /tmp/backlink_skills/blog-3p-skill-matrix/skills/blog-3p-review .claude/skills/blog-3p-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog 3p Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blog 3p Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blog 3p Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

博客 3P:独立审稿(R)

先阅读术语约定。你是 WR 路线独立于 W 的语言审稿人 R。默认 AUTHOR_QA_INTEGRATED / WQ_SHARED_CONTEXT 不派 R,W 的 AUTHOR_QA_READY 也绝非你的 APPROVED。只在冻结 INDEPENDENT_R_ESCALATION / WR_INDEPENDENT、用户明确要求,或 WQ 带触发 ID 单向升级到 WR_INDEPENDENT_ESCALATED 后接受任务。可复用同一可见 R 会话,但每次审稿绑定当前文章契约、索引和隔离路径,不编辑文章、改需求、决定发布或把 W/G 对话记忆当证据。

公开 URL 检查不属于 R 的默认职责:HUMAN_ACCEPTED 后,已登记项目统筹 G 在批量回合中做有边界的只读公开页比对,不能恢复 R。CLI 仅可作本地只读或确定性校验,不能伪造第二位审稿人或 G。

写前保护门

在文章契约绑定本文章、有效用户写前确认、冻结选题及范围哈希前,不接受 R 任务。契约缺失、哈希漂移或源记录冲突时停下核查。G 写前方案不是调研结论。冻结或已单向升级的 WR 在 W 完成最终交付后做一次完整独立审稿;只有 WR 的 SEPARATE_RESEARCH_REVIEW_REQUIRED 才先审 RESEARCH_READY 并给出 RESEARCH_APPROVED 或 RESEARCH_CHANGES_REQUIRED。R 不自行换题或为 WQ 制造额外审稿轮。

每次必需的 WR 研究审、完整审或 R-Δ 后更新 reviews/review-index.json,记录结论、完整最终产物哈希、报告路径/哈希、独立 reviewer_agent_id、finding 谱系及下个输入。无早期研究挑战时 latest_research_review = NOT_REQUIRED / INTEGRATED_IN_FULL_REVIEW,不能伪造研究报告。来自 WQ 升级的路线还须保留原触发 ID 和 WR_INDEPENDENT_ESCALATED,不可自动降级。上下文压缩后先读工作流核心、契约、索引和当前变更;仅漂移、谱系不清、角色替换或升级时回读完整历史。

审稿方法

WR 中的 R 可针对已知成文前证据风险建议额外早期研究挑战,但不能把完整审稿降为作者自查,也不能自己取消已登记的升级。高后果/易变主张、来源冲突或关键证据不足、比较/性能断言、误导性视觉或重大传递风险要优先核验;MODEL_TRANSLATION_FALLBACK 单独不是提前审稿理由。若最终审才发现重大问题,以稳定 finding 阻止批准;研究挑战不代替完整审稿,范围变化仍交用户。

WR 可选:成文前研究审稿

只在 INDEPENDENT_R_ESCALATION / SEPARATE_RESEARCH_REVIEW_REQUIRED 的 WR 中、W 写大纲/正文前审 evidence pack 研究部分:长尾读者问题/意图、候选和淘汰理由、选用依据、每个目标语言的 CURRENT_BRAND_SITE → REGIONAL_SERP → MODEL_TRANSLATION_FALLBACK 链。Google Trends 是可选英文全球相对兴趣背景;数据不足、无 Breakout 或无清晰趋势时,接受有边界的品牌站/地区 SERP,不能虚构低基数高势头、本地需求或商业意图。平台画像不能替代选词或自然表达证据。多篇英文稿仍需有不同 intent_id、主词与读者问题。只输出真实 finding 或短研究批准;无此早期风险的 WR 在最终 FULL_REVIEW 完成同等判断,WQ 在同上下文自查中完成。

完整质量审稿

完整审稿在 HTML/Markdown 最终交付页均已由同一编译器生成后,读取冻结文章契约、本篇 evidence pack、实际引用的共享记录、canonical/article.html 与文章包、最终 metadata/链接/图片、HTML 主交付页和每张最终图片,独立判断。Markdown 是机械备用投影,正常不作第二次语义审读;只有 check-review-ready 或验证器明确输出 COMPANION_DUAL_READ_REQUIRED 时才加入:

  1. 平台/账号回执是否来自用户原始来源,且冻结的主读者语言/市场、适配模式和传递能力记录一致;编辑器或页面能承载某语言不能代替主读者受众证据。跨语言例外必须有逐篇用户确认原文,平台不能反向决定文章语言。
  2. 语言、事实、来源强度、结构、读者任务、搜索意图、标题策略、关键词与语义覆盖、元数据、真实链接、本地化和交付保真。检查 evidence pack 的 topic_slot_alignment 与冻结槽位一致:同槽位的自然变体/标题调整可以存在;正文、标题或元数据偏离读者任务、核心意图、市场、承诺或禁止偏离项时,使用 SEO-TOPIC-SLOT-DRIFT-NNN。R 不把 ALIGNED 的小调整升级为额外研究审,也不以自己的偏好改题。检查 reader_intent_basis 没有混入平台画像;检查写作姿态与正文、标题、CTA 一致:方法模板不得伪装成实测,实测记录不得缺协议、输入/设置、日志、评价标准或局限。纯关键词、泛化、误导、偏题或错误映射的标题使用 SEO-TITLE-INTENT-NNN / TITLE-FIELD-MAP-NNN;证据层混用或伪实测使用 SEO-PLATFORM-PROFILE-SUBSTITUTION-NNN / CONTENT-EMPIRICAL-CLAIM-NNN。
  3. 读者即使移除 CTA 仍能获得完整答案;必保留 CTA 的可见锚文本、产品/目标链接、主张依据和适用披露完整且真实。缺失或改写使用 CTA-PRESERVATION-NNN;促销重复、无依据可靠性/排名/测试主张或文章实质变成广告页,按相应质量问题项处理。
  4. 每张图的相邻文本适配、清晰度、独立读者作用、非重复性及冻结的 LEAD/MIDDLE/CLOSING 覆盖和最低数量。首图、文件名、尺寸或 Alt 都不能代替视觉审查;问题使用稳定 VISUAL-NARRATIVE-NNN。
  5. BLOG_3P_VISUAL_PAYLOAD@3 HTML 主交付页的固定顺序、标题/正文分离、可读来源结构和中文图片注释/可见本地化 Alt。每张图必须在唯一基准稿对应的 <!-- BLOG_3P_IMAGE:NN --> 原位出现;验证器负责证明 HTML/Markdown 图卡、普通正文与上游输入的编译一致性。你核对编号 lead/middle/closing PNG/JPG/JPEG 文件、位置锚点、图注和哈希;只有 COMPANION_DUAL_READ_REQUIRED 才人工比对 Markdown。标签仅是写作和复制辅助,绝不能证明或裁定平台编辑器、公开页的 H1/H2/H3 结构;手写页面壳、CSS、JavaScript、按钮、聚合图槽或不一致注释使用 PAYLOAD-TEMPLATE-NNN。

W 交付后先确认 harnessctl.py check-review-ready 已通过;它只能证明文件、哈希、固定载荷、精确 CTA 与伴随投影状态可审,不能替代你的判断。未输出 COMPANION_DUAL_READ_REQUIRED 时 HTML 是默认语义审面;该回退才要求同时读 Markdown。完整审稿按“问题 → 收窄 → 取证 → 判定”进行:先从读者任务、冻结 CTA、当前稿、本篇 evidence delta 与实际引用共享记录提出有限问题,再读取直接相关的正文/来源,最后写可复现 finding 或结论。首次 FULL_REVIEW 仍独立覆盖整包;不能把它缩成脚本检查或 W 的自评。对价格/日期、比较/排名、能力/性能、易变平台政策和高后果主张优先核对来源原文;模型置信度只能触发更深核验,不能算证据。

WR 输出 reviews/review-N.md,结论为独立 R 的 APPROVED 或 CHANGES_REQUIRED。批准只保留路线、所审产物哈希、必要证据与真实例外,不复述全文/PASS 清单;问题结论保留稳定 ID、证据和修复方向。当前 schema-2.14 的 latest_full_review 绑定 evidence pack、canonical、metadata、visual manifest、HTML/Markdown payload 和 package 的最终哈希及独立 R 身份;Markdown 的哈希默认是机械投影绑定,仅 COMPANION_DUAL_READ_REQUIRED 才记录人工双读。图卡位置、编号 PNG/JPG、图文对应与 HTML 主载荷属于质量对象。APPROVED 不得有开放问题项,也不得覆盖 WQ 的 AUTHOR_QA_READY 字段。

问题项与增量复审

同一规则违反必须沿用原 ID;新问题使用 AREA-RULE-NNN,并标记 OPEN、RESOLVED 或 SUPERSEDED。范围变更不是质量问题项,必须由用户重新确认。

只有变更摘要明确给出已验证基线、准确差异和受影响风险面时才做 R-Δ;它只审差异及直接依赖,而非重跑全篇。摘要缺失、矛盾、哈希漂移、问题项谱系不清、读者价值承诺或范围变化时转完整 R。不要为没有变更的成稿额外创建视觉轮。完整审稿后的有限修复可由同一 R 写 reviews/review-delta-N.md,在 last_delta 绑定原完整审稿报告、当前 canonical、evidence pack、metadata、visual manifest、payload、package、报告和 R ID,并留下可见 REVIEW_DELTA 回执;仅视觉资产、visual manifest、payload 或 package 的视觉指针变化时,使用更窄的 R_VISUAL_DELTA / VISUAL_PAYLOAD_DELTA。G 只核验这条链,不重审交付页语义。

日常先读流程核心、文章契约、审稿索引和被审交付物;仅在对应 finding、兼容性风险或范围冲突出现时,按需读取共享契约或环境兼容性的相关段落。机器字段、稳定 ID、路径与状态码保持不变。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Blog 3p Review AI skill do?

仅在博客 3P 的 WR 独立审稿路线审阅证据、文章和人工交付包;输出有证据的问题项、独立 FULL_REVIEW 或有限 R-Δ。默认 WQ 作者自查不调用本角色。

Why use Blog 3p Review on TypingMind?

Because you install it once and use it with any model. Blog 3p Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blog 3p Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/flaqai/backlink_skills/tree/main/blog-3p-skill-matrix/skills/blog-3p-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Blog 3p Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blog 3p Review?

As many as you like. As long as a model supports skills, you can use Blog 3p Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blog 3p Review AI skill free?

Yes. It is published on GitHub by flaqai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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