hiring-signal-prospector — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited hiring-signal-prospector (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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.
If the user provides partial criteria, infer reasonable defaults and confirm before proceeding.
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.
WebFetch on the top 10-15 results. For each job posting, extract:Deduplicate companies that appear in multiple postings.
mcp__claude_ai_Amplemarket__enrich_company with the domain for each unique company discovered. Extract: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.
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}} |
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. |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.