linkedin-post-generator — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited linkedin-post-generator (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Turns any input into 3 ready-to-publish LinkedIn post variants, each with a different hook style. Works standalone or chained with other intelligence skills.
Before running, set in CONFIG.md:
YOUR_VOICE_STYLE= # e.g. direct and data-driven, warm and conversational
YOUR_LINKEDIN_TONE= # e.g. insight-led, contrarian, story-driven
YOUR_BANNED_PHRASES= # e.g. synergy, leverage, game-changer, excited to share
YOUR_ICP_INDUSTRY= # Used to make posts relevant to your audience
ANTHROPIC_API_KEY=# CLI with a topic
agent run linkedin-post-generator --input "Your topic or observation here"
# CLI with no input — prompts you to enter one
agent run linkedin-post-generator
# Voice (after ACTIVATION.md setup)
"[your wake word] linkedin"
# Chain from another skill
agent run ai-news-digest | agent run linkedin-post-generator
agent run icp-radar | agent run linkedin-post-generator
# Scheduled — set your preferred days/times in crontab or Task Scheduler
# See ACTIVATION.md for scheduling instructions| Variant | Hook style | Best for |
|---|---|---|
| INSIGHT-LED | Leads with a specific number or data point | When you have a metric or result |
| STORY-LED | Opens with a scene or moment | When you have a client story or observation |
| CONTRARIAN | Challenges a common belief | When you disagree with conventional wisdom |
You are a LinkedIn content strategist. Write 3 post variants from the following input.
Voice style: [YOUR_VOICE_STYLE]
Tone: [YOUR_LINKEDIN_TONE]
Target audience: [YOUR_ICP_TITLES] in [YOUR_ICP_INDUSTRY]
Never use these words or phrases: [YOUR_BANNED_PHRASES]
Input: [USER_INPUT]
Variant 1 — INSIGHT-LED: Lead with a specific number, result, or observation.
Variant 2 — STORY-LED: Open with a scene, moment, or situation.
Variant 3 — CONTRARIAN: Challenge a commonly held belief in your industry.
Rules for all variants:
- First line must stop the scroll — no "I am excited to share"
- No more than 200 words
- One clear point per post — do not try to say everything
- End with a question that invites comments or a statement that lands hard
- No bullet point lists — write in short paragraphs
- No hashtags in the body — add them at the end only
Also return:
- hook_score for each variant (1-10)
- recommended_variant with reason
- best_posting_time (day and time window based on B2B LinkedIn patterns)
- hashtags (5 relevant ones, no more)
Return valid JSON only.{
"posts": [
{
"variant": "INSIGHT-LED",
"text": "Post text here...",
"hook_score": 8
},
{
"variant": "STORY-LED",
"text": "Post text here...",
"hook_score": 7
},
{
"variant": "CONTRARIAN",
"text": "Post text here...",
"hook_score": 9
}
],
"recommended_variant": "CONTRARIAN",
"recommendation_reason": "Strongest hook — challenges a belief your audience holds.",
"best_posting_time": "Tuesday or Wednesday, 7:30–9:00 AM your local time",
"hashtags": ["#AIMarketing", "#B2BSaaS", "#MarketingOps", "#GrowthMarketing", "#ContentStrategy"]
}# Full morning content workflow
agent run ai-news-digest | agent run linkedin-post-generator
# Lead insight to post
agent run icp-radar | agent run linkedin-post-generator
# Natural language
agent ask "Run the news digest and turn the top story into 3 LinkedIn post variants"ai-news-digest — feed today's news stories as inputicp-radar — feed lead insights as inputcompetitive-intel — feed competitor observations as inputACTIVATION.md for voice and scheduled setup~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.