andrew-shwetzer/career-ops-plugin/scan

Claude Code and agent skill by andrew-shwetzer/career-ops-plugin

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Scan company career pages for job openings that match your profile. Uses web search with site-scoped queries to find listings on Greenhouse, Lever, Ashby, SmartRecruiters, and other ATS platforms. Use when someone says 'scan for jobs', 'check careers page', 'find openings at', or 'search for roles'.

Install

npx vskill@latest install andrew-shwetzer/career-ops-plugin/scan

SKILL.md

Scan for Job Openings

Search company career portals for roles matching your profile. Use ATS type and slug detection (see references/ats-endpoints.md) to build targeted site-scoped WebSearch queries.

Step 0: Load Context

  1. Read data/profile.yml for target roles, skills, seniority
  2. Read config/portals.yml if it exists (company watchlist)
  3. Read data/scan-history.md if it exists (dedup against seen postings)
  4. Read data/applications.md to exclude roles already tracked

Step 1: Determine What to Scan

Parse user input:

  • Company name: Look up in portals.yml for ATS type and slug.

If not found, use WebSearch to find their careers page and detect ATS.

  • URL: Detect ATS type from URL pattern:
  • boards.greenhouse.io/{slug} or {company}.greenhouse.io -> Greenhouse
  • jobs.lever.co/{slug} -> Lever
  • jobs.ashbyhq.com/{slug} or {company}.ashbyhq.com -> Ashby
  • jobs.smartrecruiters.com/{slug} -> SmartRecruiters
  • Other -> use WebSearch with {company name} careers {role keywords}
  • "all" / "scan my watchlist": Scan every enabled company in portals.yml.

If no portals.yml exists, tell the user: > "You don't have a company watchlist yet. Tell me some companies > you're interested in and I'll set one up."

  • "scan {industry}": Use WebSearch to find companies hiring in that

industry, then scan their career pages.

Step 2: Fetch Job Listings

Tier 1: WebSearch (primary)

Use WebSearch with targeted site-scoped queries to find job listings. Use the ATS type and slug identified in Step 1 to build precise queries.

Search strategy by ATS:

  • Ashby: site:jobs.ashbyhq.com/{slug} {target role keywords}
  • Lever: site:jobs.lever.co/{slug} {target role keywords}
  • Greenhouse: site:job-boards.greenhouse.io/{slug} {target role keywords}

(Note: Greenhouse pages are poorly indexed. If no results, try {company name} careers {target role keywords} greenhouse)

  • SmartRecruiters: site:jobs.smartrecruiters.com/{slug} {target role keywords}
  • Workday: site:{tenant}.myworkdayjobs.com {target role keywords}
  • Generic / unknown ATS: {company name} careers {target role keywords} {current year}

Build target role keywords from the profile: combine primary_role, secondary_roles, and top 3 skills. Example for a marketing director: marketing director OR head of marketing OR VP marketing

Parse search results: Each result typically contains the job title in the link text and the URL to the posting. Extract title and URL from each search result. If the search returns descriptions, extract location and department info as well.

Run multiple queries if needed: One for the primary role, one for secondary roles. Deduplicate by URL before filtering.

Tier 2: Manual Fallback

If WebSearch fails to return results:

"I couldn't find listings automatically for {company}. Here's their
careers URL: {url}. You can browse it and paste any interesting
job postings for me to evaluate."

Step 3: Filter & Match

For each job listing found:

  1. Title relevance: Compare against target roles from profile.yml
  • Match target role keywords (primary + secondary roles)
  • Exclude roles that don't match seniority level
  • Exclude titles with negative keywords if profile has exclude_keywords
  1. Quick relevance score (0-10):
  • Title match to target roles: 0-4 points
  • Skills/keyword overlap with profile: 0-3 points
  • Location/remote match: 0-2 points
  • Seniority alignment: 0-1 point
  1. Dedup:
  • Check URL against data/scan-history.md (skip if seen)
  • Check company + title against data/applications.md (skip if tracked)

Step 4: Output

## Scan Results: {Company} - {date}
Found **{X}** openings, **{Y}** match your profile.
### Matches (by relevance)
| # | Role | Location | Relevance | Link |
|---|---|---|---|---|
| 1 | {title} | {location} | {score}/10 | {URL} |
| 2 | ... | ... | ... | ... |
### Filtered Out ({Z} roles)
{Brief list: "3 junior roles, 2 in unrelated departments, 1 requires
relocation to {city}"}

Step 5: Save & Next Steps

Add all matches to data/pipeline.md (create if doesn't exist):

markdown
# Job Pipeline
| Date Found | Company | Role | Relevance | URL | Status |
|---|---|---|---|---|---|
| {today} | {company} | {title} | {score}/10 | {url} | New |

Log ALL seen postings (matches + filtered) to data/scan-history.md:

markdown
| Date | Company | Role | URL | Action |
|---|---|---|---|---|
| {today} | {company} | {title} | {url} | Matched / Filtered: {reason} |
"Found {Y} matching roles at {company}.
Want me to:
- Evaluate the top match? Say 'evaluate #1'
- Triage the full pipeline? Say 'triage my pipeline'
- Scan another company? Say 'scan {company}'"

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Source

Popularity

Repository stars
227
Repository forks
65
7-day trend score
27

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 27 Apr 2026, 6 months ago.

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