Job Scraper

Purpose

This file is the Plane 1 knowledge anchor for the job search workflow (ARCH-0008, ARCH-0010). As a Plane 1 skill it lives under .claude/skills/job-scraper/ and provides the AI assistant with structured knowledge — it does not execute binaries or scrape via compiled code. The skill queries whatever job portals the user has configured, deduplicates results, performs a lightweight fit assessment, and presents new matches sorted by relevance. It covers REQ-1001 through REQ-1012.

The search core is country-agnostic (DEC-012, ADR-0004, NFR-0007): web search is the universal mechanism. No portal, country, locale, or site: string is hardcoded here — every target comes from the companion search-queries.md config. Pasted postings are a first-class input, never a fallback (DEC-011). The skill never fabricates postings (REQ-1012, ARCH-0007).

Trigger Phrases

• "Search for jobs" / "Find new jobs" / "Any new postings?"
• "Scrape job boards" / "Run a job search"
• /search (optionally with a focus area, e.g. /search data science)
• /scrape
• "Search broadly" / "Run all my queries"
• Any phrase about discovering new job postings

Companion Files

This skill never modifies search-queries.md; it only reads it.

Contract — Steps by Requirement

Invocation (REQ-1001)

• Default (/search, no argument): run the top 3 priority categories (Priority 1–3) from search-queries.md.
• Focus argument (e.g. /search data science): prioritize the query categories that match the focus term, then fill with the highest-priority remaining categories.
• "broad" (/search broad): run all query categories (Priority 1–4).
• Always load state (below) before issuing any search.
• No country-specific or portal-specific identifier is hardcoded in this skill; the breadth selection operates over whatever categories the user's config defines.

State Loading (REQ-1002)

Before searching, load all three sources:

1. job_scraper/seen_jobs.json — the seen registry. If the file is missing, create it with exactly {"seen": {}} (data-req §10).
2. job_search_tracker.csv (repo root) — extract the set of already-applied company + role pairs.
3. search-queries.md — the query strategy: Search Sites, Date Filter Rule, Priority 1–4 query groups, and Location Filter Tiers.

If search-queries.md still contains [UPPER_SNAKE_CASE] placeholder tokens, the profile has not been set up — tell the user to run /setup --section search rather than searching against template text.

Multi-Portal Web Search (REQ-1003)

• Build WebSearch queries by combining the user's configured portals (Search Sites) × query strings (selected priority groups) × geography (from the queries / location tiers).
• Constrain to postings from the last 14 days (per the Date Filter Rule).
• Issue multiple searches in parallel where useful for efficiency.
• All site: targeting, portal names, and country/region terms come verbatim from the user's config — never write a literal portal name or site: string into this skill. If the user configured site:<portal> entries, use them as-is; if they listed bare portal names, fold them into the query text.

Deterministic Listing Tier (REQ-1013, NFR-0021)

If a configured portal has an adapter (ADR-0004) exposing a deterministic list() pass, prefer it: it returns structured postings (title, company, location, URL, date) without spending tokens, pre-filtering candidates before any LLM work. Feed its results into the same dedup + quick-fit steps below. Adapters are optional — when none exists, web search (above) is the universal fallback (ARCH-0005). Prefer the cheap deterministic pass over LLM calls for the listing stage wherever available (cost-aware search, NFR-0021).

Fetch & Parse (REQ-1004)

• Pre-filter before fetching (token efficiency): inspect search-result titles and snippets, discard obvious non-matches, and only WebFetch the promising ones.

• For each fetched posting, extract: { title, company, location, posting date (or "recent"), url, key requirements (brief), application deadline (if listed) }.

• On a fetch failure (gated portal, auth wall, dead link): do not error and do not abort. Prompt exactly:

  "I couldn't fetch that posting. Paste it here and I'll use that."

  Pasted postings are processed identically to fetched ones (DEC-011) — paste is first-class input.

Quick Fit Assessment (REQ-1005)

Assign each new job a lightweight three-level signal used only for sorting:

• High — role directly involves the user's core skills.
• Medium — role is adjacent to the user's experience.
• Low — role requires significant skills the user lacks.

This is explicitly NOT the full 5-dimension evaluation and NOT a numeric score — it is a sorting signal only. The full evaluation happens later in /apply.

Quick Legitimacy Flag (REQ-8003)

Alongside the fit signal, run a cheap legitimacy scan of each posting's title and snippet against the high-severity signals in trust-safety/scam-patterns.json (upfront fees, personal-data/ID/banking harvesting, off-platform redirects, money-movement, offer without process). If a strong signal appears, mark the job ⚠ Suspicious in the results so the user sees it before investing in /apply. This is a heuristic flag only — the full legitimacy gate runs in /apply (REQ-8001). Never auto-skip a flagged job (ARCH-0006); never invent a flag without the matching text (ARCH-0007).

Deduplication & State Update (REQ-1006, data-req §10, business-rules §6)

• Skip a job if its URL is already a key in seen_jobs.json, or if its company+role pair already appears in job_search_tracker.csv.

• Record every fetched job — new AND skipped — in seen_jobs.json under the key <url_or_company_title_key> (the posting URL, or a company+title combination when no stable URL exists). Each entry has exactly these fields:

  { "seen": { "<url_or_company_title_key>": { "title": "...", "company": "...", "url": "...", "first_seen": "YYYY-MM-DD", "fit": "high|medium|low", "status": "new|skipped|evaluated" } } }
  

  • status is new for a freshly surfaced match, skipped for a deduplicated/filtered-out job, evaluated once it has been handed to /apply.
  • first_seen is the ISO-8601 date the job was first recorded; do not overwrite it on later runs.

• The registry grows monotonically — entries are never removed. Only jobs not already in the registry or tracker are presented to the user.

Geographic + Date Filtering (REQ-1010, REQ-1011)

Apply the Location Filter Tiers from search-queries.md:

• Ideal / Acceptable — include normally.
• Borderline — include but flag with a commute/relocation note; do not auto-skip.
• Too far — skip (unless the posting is remote).

Date rules:

• Skip jobs with expired deadlines and closed postings.
• Include jobs with no determinable date, but flag them as "date unknown".

Presentation (REQ-1007)

Sort by fit (high → medium → low). Present:

1. Summary header: Found X new positions (Y high, Z medium, W low match).
2. A table with columns: #, Fit, Title, Company, Location, Deadline, URL.
3. For each high-match job: 2–3 bullets on why it matches, the key requirements to check, and any red flags.
4. Then ask exactly:

   "Want me to evaluate any of these in detail? Just give me the number(s)."

Detailed Evaluation Handoff (REQ-1008)

• When the user picks a number (or numbers), pass that job's URL or pasted posting text to /apply for the full 5-dimension fit evaluation.
• Mark the handed-off job's status as evaluated in seen_jobs.json — the dedup registry must stay in sync with downstream handoffs.
• The application tracker write stays in /apply (REQ-1009) — this skill never writes to job_search_tracker.csv.

Provider Resilience (NFR-0022)

If the AI provider rate-limits, errors, or becomes unavailable mid-search, stop gracefully with a clear message and whatever partial results exist — never retry-spam or spin. Keep parallelism modest; do not run high-volume headless batches that can trip provider abuse heuristics (ARCH-0005).

No Fabrication (REQ-1012, ARCH-0007)

• Present only jobs that came from real web-search results and have real URLs (or real pasted text the user supplied).
• Never invent a posting, company, or URL.
• If a search returns nothing, say so honestly — e.g. "No new postings matched your queries in the last 14 days." — rather than padding the list.