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Follow-up to #65 feedback after #52 merged CLI-first search. Step 2 now uses each portal's detail command for CLI-sourced jobs (WebFetch only for WebSearch fallbacks). Skill description reflects market-agnostic portal CLIs instead of Danish-only wording. Co-authored-by: Cursor <cursoragent@cursor.com>
167 lines
6.9 KiB
Markdown
167 lines
6.9 KiB
Markdown
---
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name: scrape
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description: >
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Finds new job postings matching your profile via installed portal-search CLIs
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(LinkedIn, local job boards, and any skills added with /add-portal). Deduplicates
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across runs. Triggers on: job scrape, find jobs, search jobs, new jobs, job search,
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scrape jobs, /scrape
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allowed-tools: Read, Write, Edit, Glob, Grep, Bash(bun --version), Bash(bun run .agents/skills/*/cli/src/cli.ts *), WebFetch, WebSearch, Agent, AskUserQuestion
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---
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# Job Scraper
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---
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## How It Works
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This skill searches job portals using the **installed portal-search CLIs** in
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`.agents/skills/` (plus WebSearch as a fallback), using queries from your profile.
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It deduplicates against previously seen jobs and the application tracker, and
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presents new matches with a quick fit assessment.
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## Invocation
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The user triggers this skill by saying things like:
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- "Find new jobs"
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- "Scrape for jobs"
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- "Any new positions?"
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- "/scrape"
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Optional arguments:
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- A focus area, e.g. "/scrape data science" or "/scrape geophysics"
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- "broad" to run all search categories, e.g. "/scrape broad"
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---
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## Execution Steps
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### Step 0: Load State
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1. Read `job_scraper/seen_jobs.json` (create if missing - start with `{"seen": {}}`)
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2. Read `job_search_tracker.csv` to extract already-applied companies+roles
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3. Read `search-queries.md` (this directory) for the search strategy
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### Step 1: Search
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Read `search-queries.md` (this directory) for the search strategy. By default, run the top 3 priority query categories. If the user said "broad", run all categories. If the user specified a focus area (e.g. "data science"), prioritize queries from that category.
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**Use the installed CLI tools as the primary search mechanism.** Fall back to `WebSearch` only for portals that do not have a CLI skill, or if `bun` is unavailable on the system.
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#### 1a. Check bun availability
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```bash
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bun --version
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```
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If this fails (bun not installed), skip to **1c (WebSearch fallback)** for all portals and note the fallback in the Step 5 output.
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#### 1b. Run CLI tools (primary — run these in parallel where possible)
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Discover all installed portal CLI skills by reading every `SKILL.md` found under `.agents/skills/*/SKILL.md`. Each file documents that portal's exact CLI flags and usage examples. **Use each portal's own documented interface — do not guess flags.** This approach automatically includes any new portals added via `/add-portal` without requiring changes to this file.
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For each installed portal skill:
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1. Read its `SKILL.md` to find the correct `bun run …` invocation and supported flags.
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2. Translate the query terms from `search-queries.md` into that portal's flag format (e.g. `--key`, `--search-string`, `--query`, filter codes — whatever the portal's SKILL.md specifies).
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3. Scope to the last 14 days using the portal's supported recency flag (`--jobage`, `--since <YYYY-MM-DD>`, `--order PublicationDate`, etc. — as documented per portal).
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4. Cap results to ~20 per call using the portal's limit flag.
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5. Use `--format json` for machine-readable output.
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Run all portal CLI calls in parallel where possible using the Agent tool. Collect all `results` arrays into a single pool for Step 2, keeping each result tagged with its source portal skill (for Step 2 `detail` lookups).
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If a CLI tool exits with a non-zero code, log the error message and continue — do not abort the whole search.
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#### 1c. WebSearch fallback
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Use `WebSearch` for:
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- Portals listed in `search-queries.md` that do **not** have a corresponding directory under `.agents/skills/`
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- Any portal whose CLI fails at runtime
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- When bun is unavailable (Step 1a failed)
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Use the site-specific query strings from `search-queries.md` directly as WebSearch queries for these portals.
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### Step 2: Fetch & Parse
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For each promising result from Step 1:
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**From CLI results:** Search output already includes title, company, location, date,
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and URL. For jobs worth a deeper look, fetch full detail with that portal's `detail`
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command (see its SKILL.md — do not guess flags) to extract **key requirements**,
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**application deadline**, and a brief description snippet.
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**From WebSearch results:** Use `WebFetch` on the posting URL and extract the same
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fields manually.
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For every candidate:
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- Skip if the URL or company+title combo already exists in `seen_jobs.json`
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- Skip if the company+role already appears in `job_search_tracker.csv`
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### Step 3: Quick Fit Assessment
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For each new job, do a rapid fit check (NOT the full evaluation from `04-job-evaluation.md` - just a quick signal):
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- **High match**: Role directly involves your core skills
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- **Medium match**: Role is adjacent to your experience
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- **Low match**: Role requires significant skills you lack
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### Step 4: Deduplicate & Store
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1. Add ALL fetched jobs (new and skipped) to `seen_jobs.json` with structure:
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```json
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{
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"seen": {
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"<url_or_company_title_key>": {
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"title": "...",
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"company": "...",
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"url": "...",
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"first_seen": "YYYY-MM-DD",
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"fit": "high/medium/low",
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"status": "new/skipped/evaluated/ranked/expired"
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}
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}
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}
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```
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2. Only present jobs NOT already in the seen list or tracker.
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### Step 5: Present Results
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Present new jobs in a table sorted by fit (high first):
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```
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## New Job Matches - YYYY-MM-DD
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Found X new positions (Y high, Z medium, W low match).
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| # | Fit | Title | Company | Location | Deadline | URL |
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|---|-----|-------|---------|----------|----------|-----|
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| 1 | High | ... | ... | ... | ... | [Link](...) |
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### High-Match Highlights
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For each high-match job, add 2-3 bullet points:
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- Why it matches your profile
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- Key requirements to check
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- Any red flags
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```
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After presenting, ask:
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> "Want me to evaluate any of these in detail? Just give me the number(s)."
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If the user picks a number, invoke the **job-application-assistant** skill workflow (fit evaluation first, then CV + cover letter if approved).
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If the run found many new jobs (roughly 8+), also suggest `/rank` - it batch-scores all new postings against the full fit framework and returns a ranked shortlist, which beats eyeballing a long table. (`/rank` sets the `ranked` and `expired` status values in `seen_jobs.json`; treat both as already-seen for dedup purposes.)
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### Step 6: Update Tracker (Optional)
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If the user decides to apply to any job, add a row to `job_search_tracker.csv`.
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---
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## Important Rules
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1. **Never fabricate job postings.** Only present jobs from actual CLI search/detail output or WebSearch/WebFetch results.
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2. **Respect deduplication.** Always check seen_jobs.json AND job_search_tracker.csv before presenting.
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3. **Focus on configured geographic area.** Skip jobs that require relocation or are clearly outside commute range.
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4. **Only open positions.** Skip postings with expired deadlines or those marked as closed.
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5. **Be efficient with detail fetches.** Don't run `detail` or WebFetch on every search hit — pre-filter by title/snippet, then fetch only promising matches.
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6. **Parallel searches.** Run portal CLI searches in parallel; use WebSearch only for gaps the CLIs don't cover.
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