list_third_party_signals: The Full Signal Catalog

This is what's actually shipping in production today, pulled from the live signal stream. The MCP returns the same shape regardless of which source the signal came from, but the data sub-object varies by signal type. Treat the lists below as the queryable surface, not as documentation aspirations.

Coverage varies by source. Sections below are ordered by fill rate — News, LinkedIn, hiring, and work milestones are the most populated and refresh fastest. SEC filings cover the 4,500-company public-co universe deeply. Glassdoor and G2 cover most companies but are thinner per-row. Web & Social is the catch-all with the noisiest coverage — start with the higher-fill sources before falling back to it.

Every row, every source, this shape:

{
  "signal_id": "00600a80-1678-459c-a213-d193c7ececf3",
  "signal_name": "Recognition",
  "signal_type": "news",
  "signal_subtype": "recognized_as",
  "association": "company",   // or "contact"
  "detected_at": "2026-06-09T00:00:00Z",
  "company": {
    "name": "Acme Corp",
    "domain": "acme.com",
    "industries": ["Pharmaceutical Manufacturing"],
    "employee_count_low": 1001,
    "employee_count_high": 5000,
    "linkedin_url": "linkedin.com/company/acme",
    "ticker": null,
    "description": null
  },
  "contact": {
    "name": "Jane Doe",
    "first_name": "Jane",
    "last_name": "Doe",
    "email": "[email protected]",
    "job_title": "VP of Marketing",
    "seniority_level": "vp",
    "department": "marketing",
    "linkedin_url": "linkedin.com/in/janedoe",
    "city": "San Francisco",
    "state": "CA",
    "country": "US"
  },  // null for company-only signals like SEC filings, news, hiring trends
  "data": { ... }  // varies by signal type, schemas below
}

The Eight Signal Sources

Every signal flows from one of eight source families currently live in the MCP. The Warmly MCP normalizes them into a single tool surface, but knowing the source helps you write better filters. Status notes below reflect the live MCP as of June 16, 2026.

Volumes are rolling 90-day totals across all tenants as of June 2026. Each row below is the detail.

1. News & Press

The widest-funnel source. Use sparingly — high noise, but the occasional recognized_as award or partners_with announcement is a relationship opener. Refresh: weekly (~2M company refresh pool).

• signal_type: news

• Top signal_subtype values: launches, partners_with, receives_award, recognized_as, expands_offices_in, invests_into, attends_event, integrates_with, is_developing, decreases_headcount_by, retires_from, leaves, hires, plus event-based variants for funding, M&A, executive moves, customer wins, and product launches.

• Distinctive data fields: title, url, body, overview, summary, article_sentence, published_at, found_at, effective_date, event, recognition, award, amount, contact, job_title, job_title_tags, headcount, financing_type, financing_type_tags, location, location_data, image_url, is_planned, product, product_data, product_tags, related_company_name, related_company_domain, ticker, vulnerability, confidence.

2. LinkedIn (Posts & Comments, by Company or Contact)

Real-time engagement intent. The signal that beats outbound — if a buyer is engaging publicly with the category, get in front of them this week, not next quarter. Refresh: company posts monthly, contact posts and comments bi-weekly (~2M company pool, ~4M contact pool).

• signal_type: linkedin-post-company, linkedin-post-contact, linkedin-comment

• signal_subtype: linkedinPost, linkedinPostComment

• Distinctive data fields: post_url, post_text, posted_date, num_likes, num_comments, comment_text, comment_url, comment_posted_at, comment_num_likes, comment_num_comments, comment_summary, comment_intent, signal_quality, parent_post, topics, tags, initiatives, pain_points, relationship_context, technologies_mentioned, competitors_mentioned.

3. Hiring Signals (Velocity, Trends, Open Roles)

Company-level. Hiring spikes are 30-60 day predictors. Watch the rate-of-change, not the absolute count. Refresh: weekly (~21M company refresh pool).

• signal_type: hiring-velocity, hiring-trends

• signal_subtype (hiring-trends): hiringSalesRoles, hiringMarketingRoles, hiringEngineeringRoles, hiringOperationsRoles, hiringAdministrationRoles, hiringLogisticsRoles, hiringStrategyRoles, hiringProcurementRoles, hiringQualityAssuranceRoles, hiringInformationTechnologyRoles, hiringCorporateCommunicationsRoles

• signal_subtype (hiring-velocity): hiringVelocity

• Distinctive data fields: hiringVelocityPct, velocityChange, netFlowRate, historicalComparison, numberOfEmployees, numberOfOpenRoles, departments, locations, seniority, contracts, sample_urls, sample_titles, top_locations, signal_strength, open_roles_count, pct_of_headcount.

4. Work Milestones (Job Changes, Promotions, Anniversaries)

Person-level. The highest-conviction third-party signal in B2B. jobChange is the one that converts. Refresh: monthly (~4M contact refresh pool).

• signal_type: workmilestone

• signal_subtype: jobChange, promotion, workAnniversary

• Distinctive data fields: new_job_title, new_job_description, new_job_location, previous_company_name, previous_company_domain, previous_job_title, previous_job_description, previous_job_location, months_since_event, work_anniversary_year, founded_new_company, event_date.

5. G2 Product Reviews

The most underused signal in outbound. Reviews of your competitors are warm leads. Filter to negative sentiment subtypes and you've got reps with a 6-month motivation window. Refresh: monthly (~2M company refresh pool).

• signal_type: g2-product-review

• signal_subtype: UsabilityIssues, MissingFeatures, ReliabilityIssues, PricingConcerns, IntegrationProblems, CustomerSupportComplaints, RecurringProductIssues, CompetitorMentions, ActiveChurn

• Distinctive data fields: product_name, headline, summary, evidence (array of quote, review_url, review_date, star_rating, reviewer_name, reviewer_title), switching_intent, decision_maker_complaint, quantified_impact, source_page_url, competitors_mentioned, relevance.

6. SEC Filings (8-K, 10-K, 10-Q, 20-F, 6-K)

Public-company event filings. Highest credibility, longest tail. The 2-4 week window between filing and competitor awareness is where the alpha lives. Refresh: weekly (~4,500 public-co refresh pool for 8-K/10-K/10-Q, ~1,000 for 20-F/6-K).

• signal_type: eight_k_filing, ten_k_filing, ten_q_filing, twenty_f_filing, six_k_filing

• Full signal_subtype vocabulary: acquisitionAnnounced, acquisitionCompleted, ceoChange, cfoChange, cooChange, ctoChange, cisoChange, cioChange, boardChange, governanceChange, materialContract, majorContractWin, majorContractLoss, debtRefinancing, capexIncrease, restructuring, restructuringCharge, layoffs, bankruptcyProceeding, aiInvestment, cloudInvestment, dataInvestment, cybersecurityIncident, cybersecurityInvestment, automationInvestment, digitalTransformation, legacyModernization, platformStrategy, productLaunch, marketExpansion, internationalGrowth, marginPressure, cashFlowConcern, customerChurn, customerConcentration, supplyChainDisruption, litigationMaterial, regulatoryInvestigation, internalControlWeakness, carbonCommitment.

• Distinctive data fields: filing_date, filing_year, fiscal_year_end, source_url, summary, excerpts, detail, metrics, pain_points, initiatives, competitors_mentioned, vendors_mentioned, technologies_mentioned, regions_mentioned, relevance, sentiment, confidence, sales_relevance, signal_category.

7. Glassdoor Reviews

Employee-side sentiment. The signal nobody on the buying side wants to admit they read, but they all do. Refresh: monthly (~2M company refresh pool).

• signal_type: glassdoor-review

• signal_subtype: glassdoorCompensationDissatisfaction, glassdoorPoorWorkLifeBalance, glassdoorHighCulturePraise, glassdoorGrowthOpportunities, glassdoorCrossFunctionalCollaborationIssues, glassdoorLackOfTransparency, glassdoorConsistentLeadershipComplaints, glassdoorRemoteWorkPraise, glassdoorOnboardingIssues

• Distinctive data fields: job_titles, glassdoor_id, glassdoor_url, total_reviews, review_date_newest, review_date_oldest, recent_reviews_count, overallCompanyRatings (ceo_approval, culture_rating, overall_rating, business_outlook, management_rating, compensation_rating, recommend_to_friend, work_life_balance_rating, career_opportunities_rating), sentiment, summary, detail.

8. Web & Social

Catch-all for owned-media intent. Highest noise, but useful for niche segments (devtools watching open-source initiatives, founder-led companies watching Reddit, public companies watching patent filings). Refresh: monthly for most sources (YouTube, Reddit, GitHub, Twitter via social_media, website intelligence, traffic, patents, financials). github-initiative covers ~15M companies; SEO/traffic covers ~15M; tech-used (when exposed) ~218M.

• signal_type: youtube-video-company, youtube-video-contact, reddit-mentions, github-initiative, patent-filing, social_media, website, website-traffic, financial

• Twitter content ships under signal_type: social_media with signal_subtype: twitter_post.

• Top signal_subtype values: youtubeVideo, twitter_post, linkedinPost, websiteUpdate, marketingChannel, brandingChange, technicalUpdate, featureUpdate, productUpdate, fundingNews, partnershipAnnouncement, eventAnnouncement, communityEngagement, noSignificantTrafficChange, trafficSurge, trafficDecline, newCorePatent, productization, intentionalExpansion, useCase, buyingIntent, brandReputation, negativeReview, industryTrend, painPoint, productFeedback, revenueDecline, earningsAcceleration.

• Distinctive data fields: source_url, post_text, post_date, videoLink, viewCount, video_title, channelTitle, commentCount, video_description, tech_areas, uspto_assignee, newest_patent_date, patent_count_recent, traffic, engagement, traffic_band, top_countries, traffic_sources, change_3mo_pct, change_mom_pct, consecutive_months, topics, upvote_ratio, total_upvotes, total_comments, subreddits, post_author, buying_stage, ceo, sector, ticker, earnings_date, buyer_persona, talk_track, recommended_actions.

What's not in the MCP yet

A handful of source families are wired into our pipeline but not yet exposed as their own signal_type. If you need them, email me — we'll prioritize based on demand:

• Bombora B2B intent topics — surge data + topic taxonomy. Native refresh: daily.

• Hacker News mentions — submission and comment surfacing. Native refresh: daily.

• SEC Form D filings — private fundraising disclosures. Native refresh: 2× daily.

• Podcast appearances — guest-spot detection across major shows. Native refresh: daily.

• Product Hunt launches — native refresh: daily.

• Federal contract awards — USAspending.gov firehose. Native refresh: daily.

• New business formation — state-of-formation filings (~10,000+ new entities/day, 50-state coverage). Native refresh: daily.

• Conference & CFP events — tech and industry conferences via confs.tech. Native refresh: daily.

• Technographic data (tech-used) — first technographic family is on the roadmap above. Native refresh: monthly, ~218M companies in pool.

• Phone numbers — phone enrichment is billed separately in the Warmly credit meter but is not exposed through the MCP yet.

• Warmly write-MCP (orchestrator) — today, the MCP is read-only. To act on signals you bridge to hubspot, outreach, customer.io, or instantly MCPs in the same chat (Claude picks the right tool). Next quarter we'll ship a Warmly write-MCP that sequences contacts back through Warmly orchestration in a single call — signals to outbound, one tool surface.

The Sort Keys That Matter

Every row carries three numbers the agent should sort on. They're inside data:

• confidence (0.0 to 1.0): how sure the extractor is that the event happened.

• relevance (0.0 to 1.0): how relevant the event is to B2B buying behavior. jobChange events score high here, generic news events score lower.

• sales_relevance (LinkedIn signals): how likely the post or comment indicates active buying intent. Higher than relevance for engagement-driven signals.

• sentiment: positive, neutral, negative. Crucial for review and Glassdoor filters.

• signal_quality: a derived bucket used by the hiring-velocity stream.

The agent default sorts by relevance DESC, detected_at DESC, confidence DESC. Override in your prompt if you want recency over relevance or vice versa.