Install the "salary-market-scanner" agent skill from https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/salary-market-scanner into .claude/skills/salary-market-scanner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "salary-market-scanner", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "salary-market-scanner" agent skill from https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/salary-market-scanner into .agents/skills/salary-market-scanner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "salary-market-scanner", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "salary-market-scanner" agent skill from https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/salary-market-scanner into .cursor/skills/salary-market-scanner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "salary-market-scanner", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "salary-market-scanner" agent skill from https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/salary-market-scanner into .gemini/skills/salary-market-scanner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "salary-market-scanner", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "salary-market-scanner" agent skill from https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/salary-market-scanner into .github/skills/salary-market-scanner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "salary-market-scanner", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "salary-market-scanner" agent skill from https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/salary-market-scanner into .opencode/skills/salary-market-scanner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "salary-market-scanner", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
salary-market-scanner
GitHub stars
2.2k
Token cost
~2.2k tokens
SKILL.md length
355 words
Files
1
Skills in repo
28
Repo updated
First seen
Licence
MIT
At a glance
Scan live job boards and salary databases to find real-time compensation data for any role and location.
Works in 3 steps: Gather inputs → Parallel salary scan → Synthesize the market picture
A user asks whats the going rate for a senior React engineer in London
SKILL.md covers Pre-flight Check (REQUIRED), Step 1 — Gather inputs, Step 2 — Parallel salary scan and Step 3 — Synthesize the market…, plus 1 more section
Calls npm; reaches levels.fyi and google.com
What it does
Salary Market Scanner is an agent skill from tinyfish-io/tinyfish-cookbook. 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.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It works with React. The repository describes itself as: A collection of sample apps and recipes built with the TinyFish web agent. Open-source examples for you to learn & build! The licence is MIT.
When your agent uses it
A user asks whats 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]
Example prompts
“s the going rate for a senior React engineer in London”
“software engineer salary Singapore”
“how much do ML engineers make”
“/salary-market-scanner”
Requirements
Node.js
Workflow steps
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 63cd841. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
npm
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
levels.fyi
google.com
linkedin.com
indeed.com
Also links to:
agent.tinyfish.ai
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Salary Market Scanner loads about 2.2k tokens when it runs. Until then it costs about 127 tokens; SKILL.md has 355 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~127
When it runs· the whole SKILL.md, loaded when a task matches
~2.2k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
Download SKILL.mdSave it as .claude/skills/salary-market-scanner/SKILL.md (or your agent's skills folder).
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?
bash
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
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.
bash
# 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
Show full SKILL.md (137 more words)Show less
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
Salary Market Scanner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
Salary Market Scanner compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
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Scan live job boards and salary databases to find real-time compensation data for any role and location. Salary Market Scanner is an agent skill from tinyfish-io/tinyfish-cookbook. Scan live job boards and salary databases to find real-time compensation data for any role and location.
When should I use Salary Market Scanner?
Salary Market Scanner fits situations like: A user asks whats 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].
How do I install Salary Market Scanner in Claude Code?
Run `npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a claude-code`. Or copy the skill folder (skills/salary-market-scanner in tinyfish-io/tinyfish-cookbook) into .claude/skills/salary-market-scanner in your project. Claude Code loads it when a task matches its description.
How do I install Salary Market Scanner in Codex?
Run `npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a codex`. Or copy the skill folder (skills/salary-market-scanner in tinyfish-io/tinyfish-cookbook) into .agents/skills/salary-market-scanner in your project. Codex loads it when a task matches its description.
Can I use Salary Market Scanner in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tinyfish-io/tinyfish-cookbook --skill salary-market-scanner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/salary-market-scanner, .gemini/skills/salary-market-scanner, .github/skills/salary-market-scanner and .opencode/skills/salary-market-scanner in your project.
What does Salary Market Scanner need to run?
Going by SKILL.md and its folder, Salary Market Scanner needs the command-line tools its instructions call (npm). Our summary lists: Node.js.
Does Salary Market Scanner access the network?
SKILL.md names 5 domains. In commands or code: levels.fyi, google.com, linkedin.com and indeed.com; the agent is likely to contact these when it follows the instructions. As links in the text: agent.tinyfish.ai. This is read from the text; nothing was executed.
Is Salary Market Scanner safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Salary Market Scanner use?
Salary Market Scanner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Salary Market Scanner use?
About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Salary Market Scanner?
Skills that share tags, products or a category with Salary Market Scanner: Airflow Plugins (astronomer/agents, 451 stars), Kitcn (udecode/kitcn, 451 stars), Add Reactions (sbusso/claudeclaw, 194 stars) and Vercel Composition Patterns (supabase/supabase, 111k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Salary Market Scanner?
tinyfish-io (a GitHub organization) maintains it in tinyfish-io/tinyfish-cookbook, which has 2,230 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 8, 2026.
Source: tinyfish-io/tinyfish-cookbook on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.