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基于 SOC 职业分类
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| name | contact-research |
| description | "condition: CRM ou enrichment tool indisponível" |
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.
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.
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:
Contact Initiated filter (last 60 days) for their actions, not your team'sIf Spark is available, use it. Spark provides:
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.
Retrieve all Sparks (not just the most recent) when the user wants to understand how this contact's engagement has evolved over time.
Pull an abbreviated account snapshot for this contact's parent company. Note:
Based on activity and signals, surface the strongest 2–3 hooks:
Contact Initiated activity (community post, product event, support ticket)Only include sections where data was actually returned. Omit sections with no data rather than filling them with guesses.
When data is rich:
## [Contact Name] — Profile
**Overview**
[2 sentences: who they are, their role, and relationship status]
**Details**
- Title: [title]
- Company: [company]
- Email: [email]
- LinkedIn: [URL]
- Other profiles: [Twitter/X, GitHub, CRM link if available]
**Scores** [If scores returned]
[All scores as raw values or percentiles]
**Recent Activity** (last 60 days) [If activity returned]
[3–5 bullets with dates]
**Website Visits** (last 12 weeks) [If visit data exists]
[Total visit count + list of pages visited]
**Spark Profile** [If Spark data is non-null]
[Persona type, background summary, influence signals]
**Segments** [If segments returned]
[List of segment names this contact belongs to]
**Account Context**
[1–2 sentences on their company's status]
**Conversation Starters**
[2–3 specific, signal-backed openers]
When data is sparse (e.g., only name, title, email, tags returned; sparkSummary is null):
## [Contact Name] — Profile (Limited Data)
**Data available:** [List exactly what Common Room returned]
[Present only the returned fields]
**Web Search**
[Any findings from searching their name + company]
**Note:** Common Room has limited data on this contact. No activity history, scores, or Spark profile available. I can run deeper web searches or look up their company for additional context.
Do not generate conversation starters, persona inferences, or engagement assessments from sparse data. These require real signals.
Contact Initiated activity (last 60 days) is the primary engagement signal — lead with itreferences/contact-signals-guide.md — full field descriptions, Spark persona guide, and conversation starter principlesTrack —
Use this skill when the task requires contact research capabilities.