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Find companies hiring for roles that signal product need, then enrich and identify decision-makers to target.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Helps sales reps break into target accounts via Amplemarket. Runs deep research on the company and key people, identifies the buying committee, surfaces possible engagement angles, recommends who to reach out to and why, and creates personalized multi-channel sequences. Use when a rep wants to research, plan, or execute outreach against a target account — net-new or re-engagement.
Interactively refine your Ideal Customer Profile through guided questions, web research, and iterative Amplemarket searches until your targeting criteria are dialed in.
Build a visual, interactive org chart for any target account using Amplemarket and HubSpot MCP data. Combines contact discovery, enrichment, outreach history, CRM deal context, and relationship signals into a single React-based visual. Use this skill whenever the user asks to map an org structure, visualize contacts at a company, understand outreach status across an account, build a stakeholder map, do account-based research, cross-reference with CRM, see account penetration with CRM data, or map a specific team. Trigger phrases include: "show me the org chart for [company]", "who do we know at [company]", "map the buying committee", "show me outreach status for [account]", "pull all contacts at [domain]", "account map", "stakeholder map", "account penetration", "engineering org chart for [company]", "map the product team at [company]", "deal context for [account]".
Map untapped departments and roles within existing accounts to surface expansion opportunities, then find contacts in whitespace areas with personalization that references your existing relationship.
Analyze existing HubSpot customer accounts to find untapped departments and personas, map whitespace against the full organizational structure from Amplemarket, and generate expansion outreach referencing the existing customer relationship.
Help AEs get a status check on their accounts with open deals -- where things stand, where to focus, and what next steps to take.
| name | hiring-signal-prospector |
| description | Find companies hiring for roles that signal product need, then enrich and identify decision-makers to target. |
| metadata | {"author":"amplemarket","version":"1.0.4","category":"Signal Monitoring"} |
| compatibility | Requires Amplemarket MCP server |
Find companies hiring for roles that signal product need, then enrich and identify decision-makers to target.
When a user wants to find companies whose job postings indicate buying intent for their product, execute this hiring-signal research workflow.
Gather signal criteria from the user. Ask:
If the user provides partial criteria, infer reasonable defaults and confirm before proceeding.
Construct WebSearch queries to find job postings across multiple sources. Run several searches using WebSearch:
"[signal role]" hiring OR "open position" OR "we're looking for" [geography]site:linkedin.com/jobs "[signal role]" [industry]site:greenhouse.io OR site:lever.co "[signal role]""[signal role]" "job description" [company size indicator]Vary the queries to maximize coverage across job boards (LinkedIn Jobs, Indeed, Greenhouse, Lever, Ashby, Workable). Run at least 3-4 different query variations to ensure broad coverage.
Fetch and extract job details by calling WebFetch on the top 10-15 results. For each job posting, extract:
Deduplicate companies that appear in multiple postings.
Analyze job descriptions for pain points. For each posting, identify:
Enrich each hiring company by calling mcp__claude_ai_Amplemarket__enrich_company with the domain for each unique company discovered. Extract:
Filter against the user's ICP. Compare enriched company data against the user's stated geography and company size preferences. Remove companies that fall outside the target criteria. Rank remaining companies by signal strength:
Find decision-makers at qualifying companies by calling mcp__claude_ai_Amplemarket__search_people with:
company_domains: [company domain]person_titles or person_seniorities: based on the user's specified decision-maker rolesfull_output: truepage_size: 5Focus on the user's stated decision-maker roles. For each company, identify 2-3 key contacts.
Present the results in a structured hiring-signal report:
Hiring Signal Summary
Company Results (table for each company):
| Field | Detail |
|---|---|
| Company | {{hiring_company_name}} |
| Domain | {{hiring_company_domain}} |
| Signal Role | {{hiring_role_title}} |
| Posting URL | {{hiring_posting_url}} |
| Posting Date | {{hiring_posting_date}} |
| JD Snippet | {{hiring_job_description_snippet}} |
| Pain Point | {{hiring_pain_point}} |
| Product Connection | {{hiring_connection_to_product}} |
| Tools Mentioned | {{hiring_tools_mentioned}} |
| Team Size Signal | {{hiring_team_size_signal}} |
| Signal Strength | Strong / Medium / Soft |
Decision Makers (per company):
| Name | Title | Suggested Opener | |
|---|---|---|---|
| ... | ... | ... | {{hiring_suggested_opener}} |
Offer to create a lead list with hiring context. If the user wants to proceed:
mcp__claude_ai_Amplemarket__create_lead_list with a descriptive name (e.g., "Companies Hiring [Signal Role] - [Date]")mcp__claude_ai_Amplemarket__add_leads_to_lead_list to add the discovered decision-makersenrich_company calls efficiently.The following dynamic fields are populated for each company discovered through hiring signals:
| Field | Description |
|---|---|
{{hiring_company_name}} | Name of the company with the hiring signal |
{{hiring_company_domain}} | Domain of the hiring company |
{{hiring_role_title}} | Exact title of the signal job posting |
{{hiring_job_description_snippet}} | Key excerpt from the job description (2-3 sentences) |
{{hiring_pain_point}} | Primary pain point inferred from the job posting |
{{hiring_team_size_signal}} | Team size or maturity indicator (e.g., "first hire", "team of 5", "scaling from 3 to 10") |
{{hiring_posting_date}} | Date the job was posted or first discovered |
{{hiring_posting_url}} | Direct URL to the job posting |
{{hiring_connection_to_product}} | How the hiring signal connects to the user's product |
{{hiring_tools_mentioned}} | Tools, technologies, or platforms mentioned in the JD |
{{hiring_suggested_opener}} | Personalized opening line referencing the hiring signal |
User prompt: "Find companies hiring SDRs - that means they're building an outbound team and need sales tools"
What the skill does:
WebSearch with queries:"SDR" OR "Sales Development Representative" hiring "open position" United Statessite:linkedin.com/jobs "SDR" OR "BDR" SaaSsite:greenhouse.io OR site:lever.co "Sales Development Representative""SDR" "first hire" OR "building outbound" "job description"WebFetch on top results to extract company names and job details.mcp__claude_ai_Amplemarket__enrich_company for each unique company.mcp__claude_ai_Amplemarket__search_people with person_titles: ["VP of Sales", "CRO", "Head of Sales"] for each company.Example output (abbreviated):
HIRING SIGNAL REPORT: Companies Hiring SDRs
Summary: 23 companies found hiring SDRs in the US. 14 match ICP after filtering. 5 strong signals, 6 medium, 3 soft.
Top Results:
| Field | Detail |
|---|---|
| Company | CloudMetrics |
| Domain | cloudmetrics.io |
| Signal Role | Sales Development Representative (First Hire) |
| Posting URL | lever.co/cloudmetrics/sdr-001 |
| Posting Date | 2026-02-28 |
| JD Snippet | "We're looking for our first SDR to build the outbound engine from the ground up. You'll define the playbook, select tooling, and establish our outbound motion." |
| Pain Point | No outbound motion exists - need to build from scratch |
| Product Connection | Building outbound from zero requires sales engagement tooling, sequencing, and prospecting platform |
| Tools Mentioned | Salesforce, LinkedIn Sales Navigator |
| Team Size Signal | First SDR hire - no existing outbound team |
| Signal Strength | Strong |
Decision Makers:
| Name | Title | Suggested Opener | |
|---|---|---|---|
| Alex Rivera | VP of Sales | linkedin.com/in/arivera | "Alex, saw CloudMetrics is hiring its first SDR. Building outbound from scratch is exciting but the tooling decisions you make now will define the team's velocity for years." |
| Jordan Lee | CRO | linkedin.com/in/jlee | "Jordan, noticed CloudMetrics is building out the SDR function. Curious what sales stack you are evaluating as you stand up the outbound motion." |
User prompt: "Who's posting jobs for data engineers? Companies investing in data infrastructure probably need our data observability tool."
What the skill does:
WebSearch with queries:"Data Engineer" hiring OR "open position" United Statessite:linkedin.com/jobs "Data Engineer" OR "Analytics Engineer" SaaSsite:greenhouse.io OR site:lever.co "Data Engineer" "data pipeline""Data Engineer" "first hire" OR "building data team" "job description"WebFetch on top results to extract company names and job details.mcp__claude_ai_Amplemarket__enrich_company for each unique company.mcp__claude_ai_Amplemarket__search_people with person_titles: ["VP of Engineering", "Head of Data", "CTO"] for each company.Example output (abbreviated):
HIRING SIGNAL REPORT: Companies Hiring Data Engineers
Summary: 31 companies found hiring Data Engineers. 18 match ICP after filtering. 7 strong signals, 8 medium, 3 soft.
Top Results:
| Field | Detail |
|---|---|
| Company | FinLedger |
| Domain | finledger.io |
| Signal Role | Senior Data Engineer (First Data Hire) |
| Posting URL | greenhouse.io/finledger/data-eng-01 |
| Posting Date | 2026-02-20 |
| JD Snippet | "We're building our data infrastructure from the ground up. You'll be our first dedicated data engineer, responsible for designing pipelines, selecting the warehouse, and establishing data quality practices." |
| Pain Point | No existing data infrastructure - building from zero with no observability |
| Product Connection | Greenfield data stack needs observability from day one to avoid data quality debt |
| Tools Mentioned | Python, SQL, AWS, "modern data stack" |
| Team Size Signal | First data hire - no existing data team |
| Signal Strength | Strong |
Decision Makers:
| Name | Title | Suggested Opener | |
|---|---|---|---|
| Priya Sharma | CTO | linkedin.com/in/psharma | "Priya, saw FinLedger is hiring its first data engineer. Building the data stack from scratch is the perfect time to bake in observability before pipeline complexity makes it painful." |
| Marcus Webb | VP of Engineering | linkedin.com/in/mwebb | "Marcus, noticed FinLedger is standing up a data function. Curious if data observability is part of the architecture plan or something you are planning to add later." |
User prompt: "Find companies hiring a RevOps Manager - that signals they're scaling and need revenue intelligence tooling"
What the skill does:
WebSearch with queries:"RevOps Manager" OR "Revenue Operations Manager" hiringsite:linkedin.com/jobs "Revenue Operations" SaaS B2Bsite:greenhouse.io OR site:lever.co "RevOps" OR "Revenue Operations""Revenue Operations" "first hire" OR "building RevOps" "job description"WebFetch on top results to extract company names and job details.mcp__claude_ai_Amplemarket__enrich_company for each unique company.mcp__claude_ai_Amplemarket__search_people with person_titles: ["CRO", "VP of Sales", "VP Revenue Operations"] for each company.Example output (abbreviated):
HIRING SIGNAL REPORT: Companies Hiring RevOps Managers
Summary: 19 companies found hiring RevOps Managers. 12 match ICP after filtering. 4 strong signals, 5 medium, 3 soft.
Top Results:
| Field | Detail |
|---|---|
| Company | ScaleFlow |
| Domain | scaleflow.com |
| Signal Role | Revenue Operations Manager (First RevOps Hire) |
| Posting URL | lever.co/scaleflow/revops-001 |
| Posting Date | 2026-03-01 |
| JD Snippet | "We're hiring our first Revenue Operations Manager to bring structure to our go-to-market engine. You'll own CRM administration, build forecasting models, and establish reporting across sales, marketing, and CS." |
| Pain Point | No formalized RevOps function - forecasting and pipeline reporting done ad hoc |
| Product Connection | Formalizing RevOps requires revenue intelligence tooling for pipeline visibility and forecasting accuracy |
| Tools Mentioned | Salesforce, Google Sheets ("migrating from spreadsheets") |
| Team Size Signal | First RevOps hire - no existing operations team |
| Signal Strength | Strong |
Decision Makers:
| Name | Title | Suggested Opener | |
|---|---|---|---|
| Dana Mitchell | CRO | linkedin.com/in/dmitchell | "Dana, saw ScaleFlow is bringing on its first RevOps hire. That transition from spreadsheets to a real revenue operations function is exactly when the right tooling makes or breaks the process." |
| Chris Nakamura | VP of Sales | linkedin.com/in/cnakamura | "Chris, noticed ScaleFlow is formalizing RevOps. Curious how you are thinking about revenue intelligence tooling as you move beyond spreadsheet-based forecasting." |
| Problem | Solution |
|---|---|
| WebSearch returns few job postings | Fallback chain: 1) Broaden the job title (e.g., add variations like "BDR" for "SDR", "Analytics Engineer" for "Data Engineer"). 2) Remove geography constraints and search globally. 3) Try different job board sites (add Ashby, Workable, JazzHR to search queries). 4) Search for the function instead of the exact title (e.g., "outbound sales" instead of "SDR"). |
| WebFetch fails to load a job posting page | Skip the page and note the company name and URL for manual review. Many job boards use JavaScript rendering that blocks fetching. Try fetching the cached or AMP version if available, or search for the same posting on a different job board. |
| Job posting appears outdated or already filled | Check the posting date. If older than 60 days, flag it: "This posting may already be filled - verify before outreach." Still enrich the company, as the hiring signal may still indicate ongoing need. |
| Too many companies found (50+) | Tighten ICP filters: narrow geography, company size, or industry. Alternatively, rank by signal strength and present only the top 15-20 strongest signals. Offer to drill into specific segments. |
| No decision-makers found at a hiring company | Fallback chain: 1) Broaden seniority to include "Manager" and "Senior". 2) Try searching by company name instead of domain. 3) For companies with <50 employees, search for "Founder" and "C-Suite" only. 4) Suggest using enrich_person with a specific name if the user has one. |
| Signal role is too niche for broad job board search | Pivot strategy: 1) Search for the broader function (e.g., "machine learning" instead of "MLOps Engineer"). 2) Use industry-specific job boards in WebSearch queries. 3) Search company career pages directly via WebFetch for known target companies. 4) Ask the user for related or adjacent roles that indicate the same buying signal. |
| Company enrichment returns minimal data | Use information from the job posting itself (company description, team size, tech stack mentions) to supplement enrichment data. Flag thin enrichment: "Limited enrichment data - company details sourced primarily from job posting." |
| User's signal hypothesis seems weak | Validate the signal before proceeding. Ask: "How confident are you that hiring for [role] indicates they need [product]? Want me to analyze a few postings first to test the hypothesis before doing the full search?" Run a small pilot search of 3-5 postings and review the JDs together before scaling up. |