Map the talent market
A talent market overview with salary ranges, employers to target, and sourcing notes.
Try this skill
Have this ready
A role title and location.
- Copy the prompt below and paste it into Claude Code.
- Follow its steps to save the skill, then share your material and ask it to help.
Claude Code with web search and file access. No external API key required. No ScoutMesh account needed.
Then ask something like
Map the market for senior DevOps engineers in Austin, Texas. Include salaries and employers to look at.
Full instructions and versions
Claude Code with web search and file access. No external API key required. If Claude cannot read the link, download the file below and save it in your working folder instead.
/rp-market-map — Competitive Landscape Mapper
Map the talent landscape for a specific role and market. Produces a structured brief covering: who competes for this talent, where these people currently work, what they earn, which skills are trending, and whether this is a buyer's or seller's market right now.
Uses WebSearch to pull real salary data, job posting volume, and market signals. Zero API cost beyond Claude usage.
Input
Parse the user's argument to extract:
role_title— the job title to map (e.g., "Senior DevOps Engineer", "Head of Product", "ML Engineer")location— city, metro, state, or "Remote US" (e.g., "Austin, TX", "New York", "Remote US")
Generate a slug from the combination: {role-slug}-{location-slug} (e.g., senior-devops-engineer-austin-tx).
If the location is missing, ask before proceeding. Location context is required for accurate comp data.
Step 1: Load Config
Check if ~/.recruiter-skills/config.yaml exists. If it does, read it. The recruiter.specialties, recruiter.target_industries, and icp fields provide context for which companies and candidates to prioritize in this map.
Step 2: Research Phase (WebSearch)
Run the following searches in sequence. For each, extract the most relevant data points. Do not include raw search result text in the output — synthesize and attribute.
2a. Compensation Data
Search queries (run 2-3 of these, pick the most data-rich results):
"{role_title}" salary "{location}" 2025 site:levels.fyi OR site:glassdoor.com OR site:linkedin.com/salary OR site:salary.com"{role_title}" compensation range "{location}" 2025"{role_title}" pay "{location}" percentile
Extract: base salary range (25th/50th/75th percentile if available), total comp if relevant (for tech roles), equity/bonus norms.
2b. Job Posting Volume and Demand
Search queries:
"{role_title}" jobs "{location}" site:linkedin.com/jobs OR site:indeed.com OR site:greenhouse.io"{role_title}" "{location}" hiring 2025
Extract: approximate number of active postings, which companies are actively hiring, how long postings have been up (proxy for difficulty to fill).
2c. Competitor Companies (Who Hires This Role)
Search queries:
companies hiring "{role_title}" "{location}""{role_title}" "{location}" team site:linkedin.com- top employers
{role_title}{location}OR remote
Extract: 8-15 specific companies that hire this exact role in this market. Categorize by type: (a) direct competitors for talent, (b) feeder companies (where candidates come from), (c) destination companies (where candidates want to go).
2d. Talent Pool Locations (Where These People Currently Work)
Search queries:
"{role_title}" "{location}" linkedin.com/in"{role_title}" professionals "{location}"where do "{role_title}" work "{location}"
Extract: The top 5-8 companies where this role concentration is highest right now. These are the hunting grounds.
2e. Skills Trends
Search queries:
"{role_title}" required skills 2025"{role_title}" job description requirements 2025what skills does a "{role_title}" need 2025
Extract: must-have skills (appearing in >70% of postings), nice-to-have skills, and skills that are declining in relevance (being replaced by newer tools/tech).
2f. Supply/Demand Signals
Search queries:
"{role_title}" talent shortage 2025 OR "{role_title}" oversupply 2025"{role_title}" hiring market 2025
Extract: Is this role in shortage (hard to fill, candidates have leverage) or surplus (many qualified applicants, clients have leverage)? Any recent layoffs or hiring freezes in this category?
Step 3: Synthesize and Write the Market Map
Format the output as a structured brief. Use these exact section headers with the separator style shown:
Step 4: Save Output
Target path: ~/.recruiter-skills/data/research/market-map-{slug}.md
Ensure the directory exists:
Write the full formatted brief to that file. Confirm the path at the end of your output.
Step 5: Suggest Next Step
After delivering the map, suggest ONE action based on what the data showed:
- If active job postings were found at specific companies: "Run
/rp-signals {company}to check for fresh hiring signals at [top company from the active hiring list]." - If the role looks hard to fill (candidate market, HARD difficulty): "Run
/rp-source {role} in {location}(requires RapidAPI key) to begin candidate sourcing with the talent pools identified above." - If the recruiter doesn't have candidates yet for this role: "Run
/rp-resume-screenwith any resumes you have to quickly identify who fits the comp and skills profile above."
Output Format Rules
- Use plain text with the separator and header style shown above. No markdown
##headers. - Attribute data sources inline when relevant ("per Glassdoor data", "based on LinkedIn job postings").
- If data wasn't findable for a section, say so explicitly: "[Could not find reliable comp data for this location/title — suggest using Levels.fyi manually for this one]"
- Do not fabricate salary figures. If search results are thin, give a range with explicit low confidence note.
- Keep the brief scannable — a recruiter should absorb it in under 5 minutes.
Need recruiting data in Claude or ChatGPT?
Use this skill for free with your own material. When you need to search recruiting data sources, connect ScoutMesh to Claude or ChatGPT. Available data and costs depend on the sources you choose.
Get started with ScoutMeshSee available sources