linkedin-hook-writer
GitHub为LinkedIn帖子生成吸引点击的真实开头,避免AI感。通过加载用户声音和反套路规则,利用具体细节、诚实承认等模式创建好奇心与质量信号,确保内容真实且符合专业规范。
Trigger Scenarios
Install
npx skills add WingedGuardian/GENesis-AGI --skill linkedin-hook-writer -g -y
SKILL.md
Frontmatter
{
"name": "linkedin-hook-writer",
"phase": 8,
"consumer": "cc_foreground, cc_background_surplus",
"skill_type": "workflow",
"description": "This skill should be used when the user asks to \"write a hook for my post\", \"give me opening lines\", \"help me start this LinkedIn post\", \"I need a better opener\", or when the linkedin-post-writer skill needs strong opening options. Also triggered by \"my posts aren't getting clicks\" or \"how do I get people to read my posts\".\n"
}
LinkedIn Hook Writer
Purpose
Generate attention-grabbing opening lines for LinkedIn posts that earn the click to "...see more" — without resorting to the clickbait patterns that mark content as AI-generated or engagement-farmed. The hook must be honest: it promises something the post actually delivers.
Voice Loading
This skill's entire value depends on producing hooks that are NOT on the anti-slop banned-openers list.
- Read
../voice-master/references/anti-slop.md— apply the Universal and Professional / LinkedIn sections. The Banned Openers subsection under Professional / LinkedIn is the hard constraint for this skill. - Load the user's voice via voice-master: read
../voice-master/SKILL.mdand follow its User Calibration Overlay section. Voice-master loads social-medium exemplars from the user overlay (or template fallback with warning if no overlay).
If no overlay is present, voice-master falls back to generic voice guidance and warns — note this in your output.
How LinkedIn Hooks Work
LinkedIn shows approximately the first 140-210 characters of a post before truncating with "...see more." The hook must accomplish two things in that space:
- Create genuine curiosity — the reader wants to know more
- Signal quality — the reader believes the rest is worth their time
A hook that creates curiosity but signals low quality gets skipped. A hook that signals quality but creates no curiosity gets polite scrolling.
Hook Patterns (Authentic)
The Specific Detail
Start with a concrete, surprising detail that makes the reader want context.
- "We migrated 340 microservices in 6 weeks. Here's what almost killed us."
- "My team's Kubernetes bill dropped 40% because of a config nobody checked."
- "I interviewed 12 candidates last month. One question separated the strong ones."
Why it works: Specific numbers and details signal real experience. The reader wants the story behind the detail.
The Honest Admission
Start by admitting something most people in your position wouldn't say.
- "I've been doing cloud architecture for 8 years and I still don't fully understand IAM policies."
- "We shipped a feature last month that I knew wasn't ready. Here's why."
- "I got fired from a job I was good at. The reason surprised me."
Why it works: Vulnerability from someone with credibility is rare on LinkedIn. It signals an honest post, not a performance.
The Counterintuitive Claim
State something that goes against conventional wisdom — but only if you can back it up.
- "The worst career advice I ever followed: 'always have an answer.'"
- "We stopped doing code reviews. Our quality went up."
- "Senior engineers who can't explain things simply aren't actually senior."
Why it works: Disrupts autopilot scrolling. The reader needs to see the reasoning.
The Observation
Notice something specific about the industry, the job, or the professional world that others feel but haven't articulated.
- "There's a specific kind of tiredness that comes from meetings about meetings."
- "Every cloud migration proposal I've seen includes the same lie."
- "The gap between 'we use AI' and 'AI is useful to us' is enormous."
Why it works: Recognition — the reader sees their own experience reflected and wants to see if the post develops it further.
The Mid-Story Start
Begin in the middle of a situation, not at the beginning.
- "The Slack message said 'production is down' and I hadn't had coffee yet."
- "Halfway through the demo, the CTO asked a question I couldn't answer."
- "The third interview round was when I realized I didn't want the job."
Why it works: Narrative momentum — the reader is dropped into a moment and wants to know what happened.
Generation Process
-
Understand the post — Read the full post content or the angle from the content calendar. The hook must honestly represent what follows.
-
Generate 3-5 options — Use different patterns. Never generate 5 variations of the same pattern — that's what AI does when it's lazy.
-
Anti-slop check — Verify each option against the banned openers list. Delete any that feel like they could appear in a "LinkedIn post template."
-
Rank — Evaluate each hook on: curiosity generated, quality signaled, authenticity, connection to the post body.
-
Present with reasoning — Show the user options with brief notes on why each works or might not work.
Output Format
## Hook Options for: [Post Topic/Angle]
### Option 1 (Pattern: [pattern name])
> [Hook text]
**Strength:** [Why this works]
**Risk:** [Why it might not — or "low risk"]
### Option 2 (Pattern: [pattern name])
> [Hook text]
...
### Recommended: Option [N]
**Reasoning:** [Why this one best fits the post and voice]
References
../voice-master/references/anti-slop.md— Banned openers and AI-tell patterns (Universal + Professional/LinkedIn sections)../voice-master/SKILL.md— Voice authority; follow its User Calibration Overlay section to load social exemplars from the user overlay../linkedin-post-writer/SKILL.md— Post types and writing process
Version History
- f9015bb Current 2026-07-05 18:17


