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 skills add Ootto-AI/claude-content-skills --skill linkedin-thought-leadershipgit clone --depth 1 https://github.com/Ootto-AI/claude-content-skillsWrote 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/ootto-ai/claude-content-skills/linkedin-thought-leadership)<a href="https://agentmods.dev/skills/ootto-ai/claude-content-skills/linkedin-thought-leadership"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/linkedin-thought-leadership/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ootto-ai/claude-content-skills/linkedin-thought-leadership"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/linkedin-thought-leadership.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00127 | $0.00652 |
| Opus 5 | $0.00063 | $0.00326 |
| Sonnet 5 | $0.00025 | $0.00130 |
| Haiku 4.5 | $0.00013 | $0.00065 |
Grade A, and why
linkedin-thought-leadership 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 12d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Thought Leadership
Turn real operating experience into a clear, useful perspective that earns attention without pretending expertise the author does not have.
1. Establish the author's right to say it
Ask what the author directly observed, built, tested, changed, or learned; who the post is for; and what evidence can be shown. Separate firsthand experience from a secondhand opinion. If the author cannot stand behind the claim, frame it as a question or choose a different source.
2. Find one teachable tension
Choose one costly misconception, surprising trade-off, operating decision, or lesson from the evidence. Explain why a reader in a similar situation should care now. The point is not to sound definitive; it is to give a useful way to make a decision.
3. Build the post around proof
Use a concrete situation, the decision made, the reasoning, the outcome or uncertainty, and the takeaway. Keep the opening specific enough to filter for the right reader. Add an example, process, or limitation when it makes the lesson more credible.
4. Design the conversation and follow-through
End with a question only if the author can meaningfully engage with answers. Otherwise use a modest action: save the framework, compare notes, or see the approved resource. Suggest comments the author can add from real context, and specify how to learn from responses rather than chasing impressions alone.
Hard rules
- Do not invent founder stories, customer outcomes, job titles, or operating facts.
- Avoid borrowed certainty: name limits, context, and trade-offs when they matter.
- Never use engagement bait that asks for comments without a useful conversation.
- Keep promotional claims secondary to the lesson and within approved proof.
- Write in the author's actual level of authority, not a universal voice.
Failure modes
| Failure | Do this instead |
|---|---|
| The post is an abstract maxim | Lead with a real decision or observed tension. |
| The insight becomes a disguised product pitch | Teach the lesson first and use only an approved, relevant next step. |
| The author cannot defend every sentence | Remove the claim or qualify it with the real evidence. |
| Comments become a vanity loop | Ask a specific question and capture recurring answers for social-listening. |
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.
- 12d ago First seen · 46 lines · 127 tokens per session scan A f7a3bbc88967
linkedin-thought-leadership is a skill published in the GitHub repository Ootto-AI/claude-content-skills (30 stars, last pushed 20d ago), licensed MIT. It adds 127 tokens to every session and 652 once invoked, about $0.0006 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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