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DevabubakarDevabubakar/atsprep-skills/skills/linkedin-profile-polish/SKILL.md

linkedin-profile-polish

Skill0 starsChanged 22 days agoMITView on GitHub

Check and improve a LinkedIn headline and About section with ATSPrep's rules - score what's there, explain the issues, and write keyword-rich headline options from the user's real role and skills. Use when someone asks to improve, rewrite or review their LinkedIn headline, summary, About section or profile.

The file

We split this skill into the rules it gives an agent

10 rules. About 0 are common, 5 are distinctive, and 5 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  • could be automatic: a setting could enforce it
  1. Distinctive:

    Use whichever is available, in this order:

    line 18
  2. Very specific:

    ATSPrep MCP tools: If the ATSPrep MCP server (https://atsprep.com/mcp) is connected, call its tools by name.

    line 20
  3. Distinctive:

    Ask for the current headline, the About section, and the job title they want to be found for.

    line 32
  4. Very specific:

    Call check_linkedin_headline with headline (references/tools.md lists the optional fields).

    line 33
  5. Very specific:

    Call generate_linkedin_headline with role and whatever the user gave (years, skills, results with their real numbers).

    line 34
  6. Very specific:

    Call check_linkedin_about with about.

    line 35
  7. Very specific:

    If they're also job hunting, suggest the resume-ats-check skill or check_resume.

    line 37
  8. Distinctive:

    Never add a number, employer, tool, credential or result the user didn't give you.

    line 41
  9. Distinctive:

    Only add a missing keyword if the user confirms they really have that skill.

    line 42
  10. Distinctive:

    Keep the headline within LinkedIn's 220 characters and lead with the role they want to be found for.

    line 44

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

LinkedIn profile polish

Web versions: https://atsprep.com/tools/linkedin-headline-generator and https://atsprep.com/tools/linkedin-about-checker.

How to call ATSPrep

Use whichever is available, in this order:

  1. ATSPrep MCP tools. If the ATSPrep MCP server (https://atsprep.com/mcp) is connected, call its tools by name. Some clients add a prefix, e.g. mcp__atsprep__check_resume.
  2. The bundled script (needs Node 18+ and network access):
    node scripts/atsprep.mjs <tool> key=value key=@path/to/file.txt
    key=@file sends a file's text, which is the safe way to pass a resume or job post. Write the user's text to a file in the current working directory first, and delete it when you're done. node scripts/atsprep.mjs list lists the tools.
  3. Plain HTTPS (no Node): POST JSON-RPC to https://atsprep.com/mcp with headers Content-Type: application/json and Accept: application/json, text/event-stream, and the body {"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"<tool>","arguments":{...}}}.

Arguments and limits for every tool are in references/tools.md. What leaves the machine is in references/privacy.md. Tell the user before sending their text to an AI tool the first time.

Steps

  1. Ask for the current headline, the About section, and the job title they want to be found for.
  2. Call check_linkedin_headline with headline (references/tools.md lists the optional fields). Explain each issue in a line or two.
  3. Call generate_linkedin_headline with role and whatever the user gave (years, skills, results with their real numbers). Offer three or four options and say why each works.
  4. Call check_linkedin_about with about. Walk through the findings: the opening lines shown before "see more", keywords, proof and a call to action.
  5. Help rewrite the About section in the user's voice, using only facts they've given. Run check_linkedin_about again on the new version.
  6. If they're also job hunting, suggest the resume-ats-check skill or check_resume.

Honesty rules

  • Never add a number, employer, tool, credential or result the user didn't give you. If a line would be stronger with a number, ask for it.
  • Only add a missing keyword if the user confirms they really have that skill.
  • AI tool results come back already filtered for made-up facts. Hold your own edits to the same standard.
  • Keep the headline within LinkedIn's 220 characters and lead with the role they want to be found for.

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

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