Linux.do Application Writer

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name: linuxdo-application description: > Craft high-pass-rate, de-AI'd Chinese applications (小作文) for Linux.do registration. Conducts an adaptive survey to learn the applicant's real background, then generates natural, rule-compliant plain text ready to paste. All user interactions in Chinese. metadata: openclaw: emoji: "📝" homepage: "https://github.com/Fei2-Labs/skill-genie" version: "1.0.0" category: "content-generation" author: "Skill Genie" license: "MIT" language: backend: English user-facing: Chinese

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Linux.do Application Writer

Generate a natural, high-pass-rate registration application for Linux.do through an adaptive interview followed by rule-aware, de-AI'd text generation.

Triggers

"write linux.do application"

"linux.do 小作文"

"linux.do 注册申请"

"help me apply to linux.do"

Quick Reference

| Input | Output | Duration | |-------|--------|----------| | Answers to 5-8 survey questions | Plain text Chinese application (~80-150 chars) | 5-10 min |

Process

Phase 1: Applicant Survey

Conduct an adaptive interview in Chinese to collect the 4 required info blocks. Ask one question at a time. Adapt follow-ups based on answers.

Core questions (ask in Chinese, adapt order based on flow):

1. 你平时主要做什么？（工作、学习、兴趣方向） 2. 你是怎么知道 Linux.do 的？（搜索、朋友推荐、看到某个帖子？） 3. 你在上面浏览过哪些内容？有没有印象深的帖子或话题？ 4. 为什么现在想注册？有什么具体的需求或场景吗？ 5. 注册之后你打算怎么用？（潜水、回帖、关注某类话题、分享经验？）

Adaptive rules:

If an answer is vague (e.g., "想学习交流"), probe deeper: "具体想学什么？在哪看到过相关讨论？"

If an answer already covers multiple blocks, skip redundant questions

If the applicant mentions a specific post/topic, ask them to elaborate — this is gold

Stop when all 4 info blocks are covered (see references/linuxdo-rules.md)

Verification: Before moving to Phase 2, confirm internally:

[ ] Background covered (what they do/follow)

[ ] Discovery path covered (how they found the site)

[ ] Join reason covered (why register now, specific scenario)

[ ] Usage plan covered (what they'll do with the account)

If any block is missing, ask one more targeted question.

Phase 2: Draft Generation + Risk Check

Generate the application draft using collected info.

Generation rules: 1. Write in first person, casual Chinese — like telling a friend why you signed up 2. Target 80-150 characters. Not too short (looks lazy), not too long (looks try-hard) 3. Weave all 4 info blocks naturally — do NOT use a 4-paragraph structure 4. Use the applicant's own words and phrasing where possible 5. No greetings, no sign-offs, no "你好" or "谢谢" — just the substance 6. Allow sentence fragments, colloquialisms, and imperfect grammar 7. Vary sentence length: mix short punchy lines with longer ones

Risk check — scan the draft against these (see references/linuxdo-rules.md):

| Risk Level | Check | |------------|-------| | HIGH | Does it mention background? Discovery path? Join reason? | | HIGH | Is there any concrete fact, or is it all fluff? | | HIGH | Does it look like a template that could apply to anyone? | | MEDIUM | Is it only admiration/flattery without substance? | | MEDIUM | Is it only "I can contribute X" without explaining why here? | | MEDIUM | Is info density too low for the character count? |

If any HIGH risk is triggered, rewrite before proceeding.

Phase 3: De-AI Polish + Final Output

Run the draft through the full de-AI checklist (see references/de-ai-checklist.md).

Audit steps: 1. Check all 12 AI markers — flag and rewrite any matches 2. Read the text as if you're a human reviewer — does it smell like AI? 3. Apply the 3-question smell test: - Could you swap details and reuse this for someone else? → too generic - Does every sentence add new information? → cut filler - Would you text this to a friend? → loosen if too formal

Output: Present the final application as plain text in a code block. Tell the user in Chinese: "这是你的申请文，可以直接复制粘贴到注册页面。"

If the user wants changes, revise and re-run Phase 3 checks.

Anti-Patterns

| Avoid | Why | Instead | |-------|-----|---------| | Parallel structures (我喜欢X，我热爱Y) | AI marker #1 | Vary grammar patterns | | 三段式 (首先/其次/最后) | AI marker #2 | Drop scaffolding | | AI vocab (赋能/深耕/沉淀/赛道) | AI marker #5 | Use plain spoken Chinese | | Flattery (久仰大名/慕名而来) | High-risk per rules | Replace with real discovery story | | Generic motivation (想学习交流) | Medium-risk per rules | State specific use case | | Press-release tone | AI marker #9 | Add 吧/嘛/其实/反正 |

Verification

After final output, confirm:

[ ] All 4 info blocks present

[ ] 80-150 characters

[ ] Zero high-risk patterns

[ ] Passes all 12 de-AI markers

[ ] Reads like a real person wrote it

[ ] Plain text, no formatting

Extension Points

1. Rule updates: When Linux.do changes registration rules, update references/linuxdo-rules.md 2. New AI markers: As AI detection evolves, add markers to references/de-ai-checklist.md 3. Multi-community: Adapt the survey + rule framework for other invite-only communities

References

Linux.do Rules & Signals — official rules + community patterns

De-AI Checklist — 12 AI markers to detect and fix

Related Skills

| Skill | Use When | |-------|----------| | wechat-compliance-check | Need to check Chinese content for platform compliance | | psychology-master | Need deeper user profiling during survey | | humanizer-zh | Additional de-AI processing for Chinese text |