MCPInstall

salary-market-scanner

Scan live job boards and salary databases to find real-time compensation data for any role and location. Use this skill when a user asks "what's the going rate for a senior React engineer in London", "software engineer salary Singapore", "how much do ML engineers make", "what should I be earning as a [role]", "is my salary competitive", "what does [company] pay for [role]", "salary range for [job title] in [city]", or any request to find out what a role pays in a specific market.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/tinyfish-io/tinyfish-cookbook --skill salary-market-scanner
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads salary-market-scanner automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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Scrape live job boards and salary databases to find real compensation data for any role and location — not outdated surveys, but what companies are actually posting and paying right now.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


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.


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

Before running, replace:

  • {ROLE} — human-readable e.g. Senior Software Engineer
  • {ROLE_ENCODED} — URL-encoded e.g. Senior%20Software%20Engineer
  • {ROLE_SLUG} — Levels.fyi slug e.g. software-engineer
  • {ROLE_INDEED} — Indeed format e.g. software-engineer
  • {LOCATION} — e.g. London, Singapore
  • {LOCATION_ENCODED} — URL-encoded e.g. London%2C%20England
  • {COUNTRY} — country code for Levels.fyi e.g. GB, SG, US

Step 3 — Synthesize the market picture

Combine data from all sources and calculate aggregate ranges.

## Salary Market Report — {ROLE} · {LOCATION}

*Live data scraped from Levels.fyi, Glassdoor, LinkedIn, and Indeed*
*{date} · Based on {N} total data points*

---

### 💰 Compensation Summary

| | Low | Median | High |
|---|---|---|---|
| **Base Salary** | {low} | {median} | {high} |
| **Total Comp** (incl. bonus/equity) | {low} | {median} | {high} |

> All figures in {CURRENCY}. "Total comp" includes base + annual bonus + annualized equity where data is available.

---

### 📊 By Experience Level

| Level | Typical Base |
|---|---|
| Entry (0-2 yrs) | {range} |
| Mid (3-5 yrs) | {range} |
| Senior (6+ yrs) | {range} |
| Staff / Principal | {range} |

*(Skip levels where no data was found)*

---

### 🏢 What Companies Are Posting

From active LinkedIn job listings with disclosed salaries:

| Company | Role | Posted Range |
|---|---|---|
| {company} | {title} | {range} |

---

### 🏆 Top Paying Companies

*(From Levels.fyi and Glassdoor)*
| Company | Median Base | Median Total |
|---|---|---|
| {company} | {base} | {total} |

---

### 📈 Market Signals

{2-3 sentences on what the data says about this market — is it competitive, is there a wide spread, are companies being transparent about pay?}

---

### 🔍 Data Sources
- Levels.fyi: {sample_size} data points / not found
- Glassdoor: {report_count} salary reports / not found  
- LinkedIn: {N} active listings with disclosed salaries
- Indeed: {report_count} salary reports / not found

Edge Cases

  • Levels.fyi has no data for this location — lean on Glassdoor and Indeed; note that Levels.fyi skews toward US big tech
  • Role title is unusual — try common variations (e.g. "ML Engineer" → "Machine Learning Engineer", "AI Engineer")
  • Location is a small city — broaden to the country or nearest major city and note the change
  • Remote role — scrape for both the user's country and the US market, present both (remote jobs often use US pay bands)
  • Non-tech role — skip Levels.fyi (tech-only), rely on Glassdoor and Indeed
  • Salary shown in different currencies — normalize to the local currency and note conversion rate used
  • User is asking if their salary is competitive — after presenting the data, ask what they're currently earning and give a direct assessment

FAQ

What does the salary-market-scanner skill do?

Scan live job boards and salary databases to find real-time compensation data for any role and location. Use this skill when a user asks "what's the going rate for a senior React engineer in London", "software engineer salary Singapore", "how much do ML engineers make", "what should I be earning as a [role]", "is my salary competitive", "what does [company] pay for [role]", "salary range for [job title] in [city]", or any request to find out what a role pays in a specific market.

How do I install salary-market-scanner?

Run npx skills add https://github.com/tinyfish-io/tinyfish-cookbook --skill salary-market-scanner in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/salary-market-scanner/ (personal) or .claude/skills/salary-market-scanner/ (project).

Which AI agents can use salary-market-scanner?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is salary-market-scanner safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains salary-market-scanner?

It is published by tinyfish-io in tinyfish-io/tinyfish-cookbook. It has 39 recorded installs.

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