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 assafkip/kipi-system --skill linkedin-brandgit clone --depth 1 https://github.com/assafkip/kipi-systemWrote 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/assafkip/kipi-system/linkedin-brand)<a href="https://agentmods.dev/skills/assafkip/kipi-system/linkedin-brand"><img src="https://agentmods.dev/badge/skills/assafkip/kipi-system/linkedin-brand/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/assafkip/kipi-system/linkedin-brand"><img src="https://agentmods.dev/badge/skills/assafkip/kipi-system/linkedin-brand.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 139 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00035 | $0.02263 |
| Opus 5 | $0.00017 | $0.01131 |
| Sonnet 5 | $0.00007 | $0.00453 |
| Haiku 4.5 | $0.00003 | $0.00226 |
Grade A, and why
linkedin-brand 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 3d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Brand Skill
This skill is the operating system for a founder's LinkedIn presence and broader LLM visibility. It enforces the 2026 algorithm reality (360Brew decoder-only LLM), provides summary frameworks, and governs the cross-platform entity graph that makes a founder legible to ChatGPT, Claude, Gemini, and Perplexity.
When to Invoke
Auto-fire on any of these:
- Drafting a LinkedIn post, article, or carousel
- Writing a comment, reply, or quote-post reacting to someone else's LinkedIn content
- Drafting a LinkedIn DM
- Writing or editing the LinkedIn About section
- Auditing the founder's LinkedIn profile
- Planning LLM visibility, personal-site schema, or third-party mention pipeline
- Any question containing "LinkedIn," "personal brand," "visibility to LLMs," or "my About section"
Skip for: internal ops chat, code, system files.
Before Drafting
Always read in this order:
references/playbook.md— format rules, cadence, first-hour rulereferences/voice-check.md— AI-detection patterns to avoidreferences/summary-frameworks.md— if drafting/editing an About sectionreferences/llm-visibility.md— if question is about broader visibility
Then read instance-specific files (not bundled in the skill):
my-project/linkedin-playbook.md— this founder's committed pillarsmy-project/linkedin-summary-template.md— this founder's current About draftmy-project/llm-visibility-plan.md— this founder's entity graph and mention pipeline
If those instance files do not exist, ask the founder to create them before drafting. Do not invent pillars or positioning.
Core Rules (ENFORCED on every draft)
Format
- Zero hashtags, or one high-intent tag max. 3+ tags costs 29% reach.
- External links go in the first comment, never the body. Body links cost 32% reach.
- Short sentences. 8-15 words average. One idea per sentence.
- Scar-anchored. Lead with real experience, not abstract claims.
- Personal-adjacent outperforms pure professional.
What ships with it
4 files 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.
- 3d ago Changed ce4599fd792a
- 11d ago First seen · 151 lines · 35 tokens per session scan A b570db426d35
linkedin-brand is a skill published in the GitHub repository assafkip/kipi-system (110 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 2,263 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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