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 WingedGuardian/GENesis-AGI --skill linkedin-profile-optimizergit clone --depth 1 https://github.com/WingedGuardian/GENesis-AGIWrote 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/wingedguardian/genesis-agi/linkedin-profile-optimizer)<a href="https://agentmods.dev/skills/wingedguardian/genesis-agi/linkedin-profile-optimizer"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/linkedin-profile-optimizer/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/wingedguardian/genesis-agi/linkedin-profile-optimizer"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/linkedin-profile-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00064 | $0.01104 |
| Opus 5.5 | $0.00026 | $0.00442 |
| Sonnet 5.5 | $0.00013 | $0.00221 |
| Haiku 4.5 | $0.00006 | $0.00110 |
Grade A, and why
linkedin-profile-optimizer 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 1mo 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Profile Optimizer
Purpose
Analyze and rewrite LinkedIn profile sections to clearly communicate the user's value to their target audience — whether that's employers, clients, or professional network. Avoid generic "results-driven professional" language. Sound human. Sound like the user.
Voice Loading
Before writing any profile content, load the user's voice via voice-master's overlay resolution:
- Read
../voice-master/SKILL.mdand follow its User Calibration Overlay section to load the user's exemplars and voice-dimensions from the out-of-repo overlay (or template fallback with warning if no overlay). - This skill's medium is
professional. Select professional-medium exemplars from whatever voice-master loads. - Read
../voice-master/references/anti-slop.md— apply the Universal and Professional / LinkedIn sections.
If no overlay is present, voice-master falls back to the generic template and warns — note this in your output.
Profile copy follows the same anti-slop rules as posts. A profile that reads like a ChatGPT template is worse than an outdated one.
Profile Sections
Headline (220 characters max)
The most visible element. Appears in search, comments, connection requests.
Formula: [What you do] | [For whom or in what domain] | [Differentiator]
Rules:
- No "passionate about" or "driven by"
- Concrete role or capability, not aspirational fluff
- Include keywords recruiters/prospects actually search for
- Test: would this make someone click on the profile?
About / Summary (2,600 characters max)
First-person narrative. Not a resume summary — a conversation with the reader.
Structure:
- Open with what you actually do and why it matters (2-3 sentences)
- Middle: specific experience, achievements, or expertise areas with enough detail to be credible (not a bullet list of buzzwords)
- Mention what you're looking for or interested in — gives people a reason to reach out
- End with how to get in touch or what kind of conversations you welcome
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.
- 1mo ago First seen · 140 lines · 64 tokens per session scan A a09cbb4ee60d
linkedin-profile-optimizer is a skill published in the GitHub repository WingedGuardian/GENesis-AGI (99 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 1,104 once invoked, about $0.0003 per session on Opus 5.5. 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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