salary-market-scanner

Salary Market Scanner

Scrape live job boards and salary databases to find real compensation data for any role and location — not outdated surveys, but what companies are actually posting and paying right now.

Pre-flight Check (REQUIRED)

Before making any TinyFish call, always run BOTH checks:

1. CLI installed?

which tinyfish && tinyfish --version || echo "TINYFISH_CLI_NOT_INSTALLED"

If not installed, stop and tell the user:

Install the TinyFish CLI: npm install -g @tiny-fish/cli

2. Authenticated?

tinyfish auth status

If not authenticated, stop and tell the user:

You need a TinyFish API key. Get one at: https://agent.tinyfish.ai/api-keys

Then authenticate:

tinyfish auth login

Do NOT proceed until both checks pass.

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Step 1 — Gather inputs

You need:

• Job title / role — e.g. Senior Software Engineer, ML Engineer, Product Designer, DevOps Engineer
• Location — e.g. London, Singapore, San Francisco, Remote
• Years of experience (optional) — e.g. 3-5 years, senior, entry level
• Specific company (optional) — if the user wants to know what a specific company pays

If location is not provided, ask before proceeding. Salary data varies dramatically by market.

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Step 2 — Parallel salary scan

Fire all agents simultaneously. Sources vary by location — include the most relevant ones.

# Agent 1 — Levels.fyi (best for tech roles, especially US/global big tech)
tinyfish agent run \
  --url "https://www.levels.fyi/t/{ROLE_SLUG}/?country={COUNTRY}" \
  "You are on Levels.fyi showing compensation data for {ROLE} in {LOCATION}.
   Extract:
   - Median total compensation
   - Base salary range (p25 to p75)
   - Bonus range
   - Stock/equity range (if shown)
   - Sample size (number of data points)
   - Top companies listed and their compensation ranges
   - Any breakdown by years of experience if visible
   STRICT RULES:
   - Do NOT click any company or individual entry
   - Read only the aggregate data visible on the page
   - If no data for this location, return {found: false, reason: 'no data for location'}
   Return JSON: {found: bool, median_total, base_p25, base_p75, bonus_range, equity_range, sample_size, top_companies: [{company, base, total}], yoe_breakdown: []}" \
  --sync > /tmp/sal_levels.json &

# Agent 2 — Glassdoor salaries
tinyfish agent run \
  --url "https://www.google.com/search?q=glassdoor+{ROLE_ENCODED}+salary+{LOCATION_ENCODED}+site:glassdoor.com/Salaries" \
  "You are on Google search results. Find the most relevant Glassdoor salary page for {ROLE} in {LOCATION} and click it.
   On the Glassdoor salary page extract:
   - Median base salary
   - Salary range (low to high)
   - Number of salary reports
   - Additional pay (bonus, profit sharing) range if shown
   - Top companies paying for this role if listed
   STRICT RULES:
   - Click only the first Glassdoor salary result
   - Do NOT click any other links after landing on Glassdoor
   - Read only the aggregate salary data visible on the page
   - If the page asks you to sign in, extract whatever is visible before the gate
   Return JSON: {median_base, salary_low, salary_high, report_count, additional_pay_range, top_companies: [{company, salary}]}" \
  --sync > /tmp/sal_glassdoor.json &

# Agent 3 — LinkedIn Jobs (extract posted salary ranges from active listings)
tinyfish agent run \
  --url "https://www.linkedin.com/jobs/search/?keywords={ROLE_ENCODED}&location={LOCATION_ENCODED}&f_SB2=1&sortBy=DD" \
  "You are on LinkedIn job search results for {ROLE} in {LOCATION}, filtered to show salary information, sorted by date.
   For each job listing card visible on the page:
   - Click into the listing to open the job detail panel on the right
   - Look for the salary range in the detail panel (often shown near the top under the job title)
   - Extract: job title, company name, salary range, employment type
   - Go back to the listing and repeat for the next one
   STRICT RULES:
   - Only extract listings that show an explicit salary — skip those without
   - Maximum 10 listings then stop
   - Do NOT navigate away from the search results page
   Return JSON array: [{title, company, salary_range, employment_type}]" \
  --sync > /tmp/sal_linkedin.json &

# Agent 4 — Indeed salaries
tinyfish agent run \
  --url "https://www.indeed.com/career/{ROLE_INDEED}/salaries?from=top_sb&l={LOCATION_ENCODED}" \
  "You are on Indeed's salary page for {ROLE} in {LOCATION}.
   Extract:
   - Average base salary
   - Salary range (low to high)
   - Number of salary reports
   - Salary by experience level (if shown: entry, mid, senior)
   - Top paying companies for this role (if listed)
   STRICT RULES:
   - Do NOT click any links
   - Read only the aggregate data on this page
   Return JSON: {average_salary, salary_low, salary_high, report_count, by_experience: [{level, salary}], top_companies: [{company, salary}]}" \
  --sync > /tmp/sal_indeed.json &

wait

echo "=== LEVELS ===" && cat /tmp/sal_levels.json
echo "=== GLASSDOOR ===" && cat /tmp/sal_glassdoor.json
echo "=== LINKEDIN ===" && cat /tmp/sal_linkedin.json
echo "=== INDEED ===" && cat /tmp/sal_indeed.json