Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/techwolf-ai/ai-first-toolkit/write-linkedin-postnpx skills add techwolf-ai/ai-first-toolkit --skill write-linkedin-postgit clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/write-linkedin-post)<a href="https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/write-linkedin-post"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/write-linkedin-post.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00032 | $0.00725 |
| Opus 5 | $0.00016 | $0.00362 |
| Sonnet 5 | $0.00006 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
write-linkedin-post scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write LinkedIn Post
You are helping write a LinkedIn post for the author.
Before Writing (MANDATORY)
You MUST complete these steps before writing ANY content:
- Run
./scripts/print-published.sh linkedin-postto read ALL published posts in one call- This is critical to avoid repeating topics or angles already covered
- Note the core insights and data points already used
- Identify opportunities to reference or build on previous posts
- Pay attention to recent patterns (last 5-10 posts) to avoid repetitive structures, hooks, or phrases
- Read
guidelines/linkedin.mdfor style rules - Read
references/professional-profile.mdfor background
If developing an idea-stage post: Check if the idea's core insight or data points overlap with published posts. If so, either:
- Find a genuinely different angle
- Explicitly build on the previous post ("In my last post I discussed X. Here's the flip side...")
- Recommend against developing the idea
Avoid Repetitive Patterns
When reading recent posts, actively note and vary:
Hooks: If recent posts start with similar patterns, try a different structure Sentence patterns: Vary rhythm - don't always use short punchy sentences or always use longer flowing ones Closing lines: Don't repeat formulas Transition phrases: Rotate between "Here's what...", "The pattern...", "This matters because...", etc. Structure: If recent posts all use problem-solution-takeaway, try a different arc
The goal is a consistent voice with varied execution. Each post should feel fresh while still sounding like the author.
Style Requirements
- Target word count per
guidelines/linkedin.md(typically 150-250 words) - Personal hook first (under 210 characters before "see more")
- Specific > abstract
- Conversational tone
- No hype words ("revolutionary", "game-changing")
Hook Priority
- Personal anecdote
- Company experience
- Surprising outcome
- Counterintuitive framing
Process
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 86 lines · 32 tokens per session scan A f61cd0147eb5
write-linkedin-post is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (96 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 725 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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