nomad3/Marketing Signal Scoring
apps/api/app/skills/native/marketing_signal_rubric/SKILL.md
--- name: Marketing Signal Scoring engine: markdown version: 1 category: marketing tags: [marketing, engagement, intent, signals] auto_trigger: "Score leads based on marketing engagement and buying intent signals" inputs: - name: entity_id type: string description: "Knowledge entity UUID to score" required: true --- ## Description Score leads 0-100 based on marketing engagement, campaign response, and buying intent signals. ## Scoring Rubric (0-100 total) | Category | Max Point
development
Updated Apr 18, 2026
$ install --global
skillsauthnpx skillsauth add nomad3/servicetsunami-agents Marketing Signal ScoringInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 29, 2026, 1:47 PM22.0s1 file scanned
SKILL.md
- name:
- Marketing Signal Scoring
- engine:
- markdown
- version:
- 1
- category:
- marketing
- tags:
- [marketing, engagement, intent, signals]
- auto_trigger:
- Score leads based on marketing engagement and buying intent signals
- - name:
- entity_id
- type:
- string
- description:
- Knowledge entity UUID to score
- required:
- true
Description
Score leads 0-100 based on marketing engagement, campaign response, and buying intent signals.
Scoring Rubric (0-100 total)
| Category | Max Points | What to look for | |---|---|---| | engagement | 25 | Website visits, content downloads, webinar attendance, demo requests, email open/click rates | | intent_signals | 25 | Searched for competitor products, visited pricing page, compared solutions, asked for proposal | | firmographic_fit | 20 | Industry match, company size in ICP range, geography alignment, technology stack compatibility | | behavioral_recency | 15 | How recent the engagement (last 7 days = highest, last 30 = medium, 30+ = low), frequency of interactions | | champion_signals | 15 | Multiple contacts engaged, senior decision-maker involved, internal champion identified, shared content internally |
Entity to Score
- Name: {name}
- Type: {entity_type}
- Category: {category}
- Description: {description}
- Properties: {properties}
- Enrichment Data: {enrichment_data}
- Source URL: {source_url}
Related Entities
{relations_text}
Output Format
Return ONLY a JSON object with this exact structure:
{
"score": "<integer 0-100>",
"breakdown": {
"engagement": "<integer 0-25>",
"intent_signals": "<integer 0-25>",
"firmographic_fit": "<integer 0-20>",
"behavioral_recency": "<integer 0-15>",
"champion_signals": "<integer 0-15>"
},
"reasoning": "<one paragraph explaining the marketing qualification score>"
}
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