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 art2url/career-agent-skills --skill linkedin-profile-boostergit clone --depth 1 https://github.com/art2url/career-agent-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/art2url/career-agent-skills/linkedin-profile-booster)<a href="https://agentmods.dev/skills/art2url/career-agent-skills/linkedin-profile-booster"><img src="https://agentmods.dev/badge/skills/art2url/career-agent-skills/linkedin-profile-booster/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/art2url/career-agent-skills/linkedin-profile-booster"><img src="https://agentmods.dev/badge/skills/art2url/career-agent-skills/linkedin-profile-booster.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 | $0.00029 | $0.00716 |
| Opus 5 | $0.00015 | $0.00358 |
| Sonnet 5 | $0.00006 | $0.00143 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
linkedin-profile-booster 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Profile Booster
Trigger
Use when the user wants to boost their LinkedIn profile, get found by recruiters, or improve their LinkedIn presence.
Keywords: "boost LinkedIn", "LinkedIn profile", "LinkedIn makeover", "recruiter visibility", "LinkedIn headline", "LinkedIn About section", "LinkedIn summary", "LinkedIn SEO", "LinkedIn keywords", "get found on LinkedIn", "recruiter search", "LinkedIn skills", "LinkedIn profile review", "improve LinkedIn", "LinkedIn not getting views"
Key Difference from Resume
LinkedIn targets all recruiters (not one employer), allows unlimited length, uses conversational tone, and is always public. Approach differently — broader keywords, more personality, expanded detail.
Process
Step 1: Headline (220 chars max)
Formula: [Role] | [Key Expertise] | [Value Proposition]
Include terms recruiters search: job title variations, key skills, tools, certifications.
Never: "Looking for opportunities", "Open to work", or just your current job title.
Step 2: About Section (target 1,500-2,000 chars)
- Hook — first 300 chars show before "see more", make them count
- Track record — 2-3 sentences with metrics
- Key strengths — 4-5 items as bullet list or → arrows
- Current context — 1-2 sentences on what you do now
- Keyword block — searchable skills as comma-separated list
- CTA — how to reach you
Write in first person, conversational tone. Front-load the most impressive content.
Step 3: Experience Section
For each role:
- 2-3 sentence role description before bullets
- 4-6 achievement bullets (more detailed than resume, can expand)
- Tag relevant skills to each position
- Add media if available (presentations, links, articles)
Step 4: Skills Section
- Use all 50 slots
- Order by relevance and endorsement count
- Include: job-specific skills, tools, methodologies, soft skills, industry terms
- Pin top 3 most important as featured
Step 5: Profile Completeness
Ensure:
- Professional headshot (face fills ~60% of frame)
- Custom background banner
- Custom headline (not default)
- About section filled
- Current + 2 past positions with descriptions
- Education listed
- 5+ skills minimum
- Featured section with best work
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 · 95 lines · 29 tokens per session scan A 7bb9cec96d44
linkedin-profile-booster is a skill published in the GitHub repository art2url/career-agent-skills (9 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 716 once invoked, about $0.0001 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 2026-08-31.
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