/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
$ npx -y skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/salary-market-scanner
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
salary-market-scanner.SKILL.mdname: salary-market-scanner
description: 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.
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Scrape live job boards and salary databases to find real compensation data for any role and location — not outdated surveys, but what companies are actually posting and paying right now.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}` — Ind
Read more
name: salary-market-scanner description: 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.
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}` — Ind
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Repo: tinyfish-io/tinyfish-cookbook
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