| name | job-search |
| description | Search LinkedIn, Hacker News, and Twitter/X for jobs with connections, hiring manager insights, and preference-based scoring. Use when the user wants to find jobs, search for positions, or explore job opportunities. |
| allowed-tools | Read, Write, Bash, WebSearch, WebFetch, mcp__claude-in-chrome__* |
Multi-Source Job Search
A Claude Code skill for searching jobs across LinkedIn, Hacker News Who's Hiring, and Twitter/X. Scores and ranks results against your saved preferences, highlights network advantages, and saves structured output.
Phase 1: Load Preferences & Parse Overrides
Step 1: Load Profile
Follow /job-apply:answer-memory: run python3 "${CLAUDE_PLUGIN_ROOT}/scripts/job-apply-store.py" init, load preferences with preferences-get, and load location or other profile facts with profile-get. Never read or write persistent Job Apply files directly.
If no preferences found, say:
No search preferences found. Run /job-apply:job-preferences first to set your target titles, salary range, and filters.
Then STOP. Do not prompt the user to set preferences inline.
If preferences exist, load them:
{
"targetTitles": ["Staff AI Engineer", "Principal ML Engineer"],
"minBaseSalary": "$250K",
"remotePreference": "remote only",
"excludePatterns": ["junior", "associate", "intern", "entry level"],
"defaultTimeRange": "last week"
}
Step 2: Parse User Overrides
The user may pass overrides when invoking the skill:
- Time range:
last week, 2 weeks, month — overrides defaultTimeRange
- Source filter:
linkedin, hn, twitter, or any combination — limits which sources to query (default: all three)
- Keywords: any additional keywords to use alongside
targetTitles
Display the active search config before proceeding:
Search config:
- Titles: Staff AI Engineer, Principal ML Engineer
- Salary floor: $250K
- Remote: Remote only
- Exclude: junior, associate, intern, entry level
- Time range: last week
- Sources: LinkedIn, HN, Twitter
Phase 2a: LinkedIn Search (Chrome MCP)
Navigation
- Get browser context using
tabs_context_mcp
- Create a new tab using
tabs_create_mcp
- Navigate to
https://www.linkedin.com/jobs/
- Verify user is logged in — use
read_page to check for profile menu. If not logged in, say: "Please log into LinkedIn in this browser tab, then let me know when you're ready." and wait.
Build Search URL
Base URL: https://www.linkedin.com/jobs/search/
| Parameter | Purpose | Values |
|---|
keywords | Search terms | URL-encoded from targetTitles |
location | Geographic area | From profile location |
f_WT | Work type | 1 (on-site), 2 (hybrid), 3 (remote) |
f_TPR | Time posted | r604800 (week), r1209600 (2 weeks), r2592000 (month) |
f_E | Experience level | 4 (mid-senior), 5 (director), 6 (executive) |
f_JIYN | In your network | true |
sortBy | Sort order | DD (date) |
Map remotePreference:
- "remote only" →
f_WT=3
- "remote preferred" →
f_WT=2,3
- "open to hybrid" →
f_WT=2,3
- "open to all" → omit
f_WT
Map time range:
- "last week" →
f_TPR=r604800
- "2 weeks" →
f_TPR=r1209600
- "month" →
f_TPR=r2592000
Extract Job Listings (max 25)
For each job card:
- Use
read_page to read job cards from results list
- Click into job detail page using
computer with left_click
- Wait 2-3 seconds for detail page to load
- Extract: title, company, location, posted date, applicant count, work type, apply method
- Look for connection indicators — use
find with query "connections work here" or "connections at"
- Look for hiring team — use
find with query "Meet the hiring team" or "hiring manager"
- If hiring manager found, extract name, title, profile URL
- Store result, navigate back to results list
- 2-3 second delay between each job
Scrolling for More Results
LinkedIn uses infinite scroll:
- Use
computer with action "scroll", scroll_direction "down"
- Wait 2-3 seconds for new results
- Use
read_page to see newly loaded cards
- Repeat until desired count or no more results
Phase 2b: Hacker News Who's Hiring (Bash + WebSearch)
Find Current Thread
- Use
WebSearch to search for: "Ask HN: Who is hiring?" site:news.ycombinator.com {current_month} {current_year}
- Extract the thread ID from the HN URL in the search results (e.g.,
https://news.ycombinator.com/item?id=XXXXXXXX → XXXXXXXX)
If no thread found for the current month, try the previous month. If still nothing, skip HN and report it.
Fetch Comments via Firebase API
- Fetch the thread:
curl -s "https://hacker-news.firebaseio.com/v0/item/{THREAD_ID}.json"
- Parse the
kids array — these are top-level comment IDs (job postings)
- Fetch each comment (up to 50):
curl -s "https://hacker-news.firebaseio.com/v0/item/{COMMENT_ID}.json"
- 0.5 second delay between API calls
Parse Comments
HN Who's Hiring comments typically follow this format in the text field:
Company Name | Role Title | Location | Remote | Salary Range
Description text...
Apply: URL
For each comment:
- Extract company, title, location, remote status, salary from the first line (pipe-delimited)
- Extract application URL if present (look for "apply" or "http" links)
- Parse salary range if present (look for patterns like
$XXXk-$XXXk, $XXX,XXX)
- Extract the full text as description
Filter Against Preferences
Skip comments that:
- Don't match any
targetTitles (fuzzy match — "AI Engineer" matches "Staff AI Engineer")
- Match any
excludePatterns
- Don't meet
remotePreference (if "remote only", skip non-remote postings)
- Fall below
minBaseSalary (if salary is listed)
Phase 2c: Twitter/X Search (Chrome MCP)
Navigation
- Use existing browser context (or create new tab)
- Navigate to
https://x.com/search
- Verify logged in — use
read_page to check for profile avatar or compose button. If not logged in, skip Twitter entirely and continue with other sources. Report: "Skipped Twitter — not logged in."
Build Search Query
Construct a Twitter advanced search query:
("hiring" OR "open role" OR "we're hiring" OR "join our team") ("AI engineer" OR "ML engineer" OR "{title1}" OR "{title2}") ("remote") since:YYYY-MM-DD -is:reply
Map time range to since: date:
- "last week" → 7 days ago
- "2 weeks" → 14 days ago
- "month" → 30 days ago
Execute Search
- Navigate to the search URL with the query
- Wait for results to load (3 seconds)
- Switch to "Latest" tab if available
- Extract tweet content, author handle, engagement (likes/retweets), and any URLs (max 20 tweets)
- 2-3 second delays between interactions
Filter Against Preferences
Apply the same filtering as HN — title match, exclude patterns, remote, salary if mentioned.
Graceful Failure
If Twitter is inaccessible, rate-limited, or not logged in — skip entirely and continue. Report which sources succeeded and failed at the end.
Phase 3: LinkedIn Detail Extraction
For LinkedIn results that passed initial filtering, extract additional network signals:
- Connection count and names (1st-degree, 2nd-degree, alumni)
- Hiring manager name, title, profile URL
- Easy Apply availability
- Applicant count and posting age
This data feeds into the scoring in Phase 4.
Phase 4: Cross-Source Scoring
Score every result on a 0-100 normalized scale.
Scoring Rubric
| Category | Points | Applies to |
|---|
| Title match (exact vs partial) | 0-20 | All sources |
| Salary meets/exceeds floor | 0-10 | All sources |
| Remote preference match | 0-10 | All sources |
| Recency (newer = higher) | 0-5 | All sources |
| Low competition (<50 applicants) | 0-5 | All sources |
| Hiring manager listed | 20 | LinkedIn only |
| 1st-degree connections | 15 | LinkedIn only |
| 2nd-degree or alumni connections | 10 | LinkedIn only |
| Easy Apply available | 5 | LinkedIn only |
| Salary explicitly listed | 10 | HN only |
| Application URL provided | 10 | HN only |
| High engagement (50+ likes) | 10 | Twitter only |
Normalization
Max possible per source: LinkedIn 100, HN 80, Twitter 70.
Normalize all scores to 0-100:
- LinkedIn score:
raw_score
- HN score:
raw_score * (100 / 80)
- Twitter score:
raw_score * (100 / 70)
Round to nearest integer. Sort all results by normalized score descending.
Phase 5: Output
1. Terminal Display
============================================================
Multi-Source Job Search Results
============================================================
Titles: Staff AI Engineer, Principal ML Engineer
Filters: Remote only | Last week | Salary >= $250K
Sources: LinkedIn (12), HN (8), Twitter (5)
Total: 25 results | Showing top 25 by score
============================================================
Score | Source | Title | Company | Salary | Location | Signals
----- | -------- | ---------------------------- | ------------- | -------- | --------------- | --------------------------
92 | LinkedIn | Staff AI Engineer | Acme Corp | $280K | Remote | Hiring mgr, 2 connections
87 | LinkedIn | Principal ML Engineer | TechStart | $300K | SF (Remote OK) | 5 connections, Easy Apply
81 | HN | AI Engineer (Staff) | CoolStartup | $250-300K| Remote | Salary listed, Apply URL
76 | Twitter | Head of AI | DataCo | — | Remote | 120 likes
...
============================================================
Summary
- 4 with hiring managers | 8 with connections
- 3 sources queried | 0 failed
- Saved to: ~/.claude-job-searches/search-2026-02-28T14-30-00.md
============================================================
2. Markdown File
Save full details to ~/.claude-job-searches/search-{timestamp}.md:
# Job Search Results — 2026-02-28
## Search Parameters
- Titles: Staff AI Engineer, Principal ML Engineer
- Salary floor: $250K
- Remote: Remote only
- Time range: Last week
- Sources: LinkedIn, HN, Twitter
## Results (ranked by score)
### 1. Staff AI Engineer — Acme Corp (Score: 92)
- **Source**: LinkedIn
- **Location**: Remote
- **Salary**: $280K
- **Posted**: 2 days ago | 45 applicants
- **Hiring Manager**: Jane Smith (Engineering Manager) — linkedin.com/in/janesmith
- **Connections**: 2 (John Doe, Sarah Lee)
- **Apply**: Easy Apply
- **URL**: https://linkedin.com/jobs/view/123456
### 2. AI Engineer (Staff) — CoolStartup (Score: 81)
- **Source**: Hacker News
- **Location**: Remote
- **Salary**: $250-300K
- **Description**: Building next-gen AI infrastructure...
- **Apply**: https://coolstartup.com/careers/ai-engineer
...
Create the ~/.claude-job-searches/ directory if it doesn't exist.
3. Queue Append (Optional, User Confirms)
If any results scored 70+, ask the user:
{N} jobs scored 70+. Would you like me to add them to your application queue at ~/Desktop/jobs/application_queue.md?
If confirmed, append to application_queue.md under a new "## Tier 3 — Auto-Discovered" section:
## Tier 3 — Auto-Discovered
| Score | Source | Role | Company | URL | Status |
|-------|--------|------|---------|-----|--------|
| 92 | LinkedIn | Staff AI Engineer | Acme Corp | [link](https://...) | New |
| 81 | HN | AI Engineer (Staff) | CoolStartup | [link](https://...) | New |
Never modify application_queue.md without explicit user confirmation.
Safety Rules
- Never handle credentials — pause for the user to complete login, password, CAPTCHA, or MFA steps manually
- Never click Apply — this skill is for searching only, not applying
- Never create accounts — stop and inform user if account creation is required
- Respect rate limits per source:
- LinkedIn: 2-3 second delays between page loads
- HN Firebase API: 0.5 second delays between requests
- Twitter: 2-3 second delays between interactions
- Max results per source: LinkedIn 25, HN 50 comments, Twitter 20 tweets
- Graceful degradation — if any source fails, skip it and continue with the others. Report which sources succeeded and which failed at the end.
- Never modify application_queue.md without user confirmation
- HN Firebase API only — never scrape the Hacker News website directly. Always use
https://hacker-news.firebaseio.com/v0/ endpoints.
- Handle errors gracefully — if a job page fails to load, skip and continue
Example Invocations
Standard search (all sources):
User: /job-apply:job-search
Claude: [Loads preferences, searches LinkedIn + HN + Twitter, displays ranked results]
With time range override:
User: /job-apply:job-search 2 weeks
Claude: [Uses 2-week time range instead of default]
Single source:
User: /job-apply:job-search hn
Claude: [Searches only Hacker News Who's Hiring]
Multiple source filter:
User: /job-apply:job-search linkedin hn
Claude: [Searches LinkedIn and HN, skips Twitter]
With extra keywords:
User: /job-apply:job-search agentic systems
Claude: [Adds "agentic systems" to title-based keywords]
