Agent skill · research science · anthropics
contact-research
Research a specific person using Common Room data. Triggers on 'who is [name]', 'look up [email]', 'research [contact]', 'is [name] a warm lead', or any contact-level question.
Why this skill is useful
Provides specific methods and data retrieval processes for enriching contact profiles using Common Room, which the AI wouldn't reliably generate on its own.
What it needs
Requires common room account access. About 3k tokens when loaded. Last updated 2026-08-07. 23,345 stars on the source repository.
What this skill does
Contact Research Retrieve a comprehensive contact profile from Common Room. Supports lookup by email, social handle, or name + company. Returns enriched data including activity history, Spark, scores, website visits, and CRM fields. Step 1: Locate the Contact Common Room supports multiple lookup methods — use whichever the user has provided: What the user gives Lookup method --------------------- -------------- Email address Look up by email (most reliable) LinkedIn, Twitter/X, or GitHub handle Look up by social handle — specify handle type explicitly Name + company Identity resolution by name + org domain; present matches if ambiguous Name only Search by name; if multiple matches, show a brief list and ask the user to confirm If no match is found, respond: "Common Room doesn't have a record for this person." Do not speculate or fabricate profile data. Step 2: Fetch Contact Fields Use the Common Room object catalog to see available field groups and their contents. For full profiles, request all groups. For targeted questions, request only what's relevant. Key field groups to know about: Scores — always return as raw values or percentiles, never labels Recent activity — use Contact Initiated filter (last 60 days) for their actions, not your team's Website visits — total count + specific pages (last 12 weeks) Spark — retrieve all Sparks when tracking engagement evolution over time Step 3: Run Spark Enrichment (If Available) If Spark is available, use it. Spark provides: Professional background and job history Social presence and influence signals Persona classification: Champion, Economic Buyer, Technical Evaluator, End User, or Gatekeeper Inferred role in the buying process If Spark is unavailable but real activity data exists (recent actions, website visits, community engagement), infer a persona from those signals. If neither Spark nor activity data is available, classify as Unknown — do not guess a persona from title alone. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills anthropics/contact-research