AGENT SKILL
pql-framework
Methodology for defining product-qualified lead (PQL) signals, scoring, and routing.
- License 许可
- MIT
- 最近更新
- 2026-09-28
- Stars
- ★ 4
- Forks
- 4
01 前言 Front Matter
- name
- pql-framework
- description
- Methodology for defining product-qualified lead (PQL) signals, scoring, and routing.
02 资源文件 6
- 资产文件assets/content_calendar_template.md1.6 KB
- 参考文档references/brand_guidelines.md6.0 KB
- 参考文档references/content_frameworks.md10.3 KB
- 参考文档references/social_media_optimization.md8.9 KB
- 脚本scripts/brand_voice_analyzer.py6.5 KB
- 脚本scripts/seo_optimizer.py15.3 KB
03 SKILL.md 正文
PQL Framework Skill
When to Use
- Standing up or recalibrating PQL/PQA programs.
- Aligning product, growth, and sales on what constitutes a high-intent product user.
- Auditing the health of existing PQL scoring + routing logic.
Framework
- Signal Library – catalog feature usage, plan limits, collaboration signals, intent, firmographics.
- Scoring Model – weight signals, set decay rules, and define negative indicators.
- Tiering – map PQL tiers (A/B/C) to follow-up motions and SLAs.
- Routing Rules – specify owners, cues, channels (CRM tasks, Slack alerts, CS queue).
- Measurement Loop – track conversion, ARR impact, and feedback for model tuning.
Templates
- Signal inventory worksheet with data source + freshness.
- Scoring matrix with weights, thresholds, and decay logic.
- Routing decision tree linking tiers to plays.
Tips
- Start with simple tiering, iterate once telemetry + feedback improve.
- Include “disqualifier” signals (expired trials, churn risk) to avoid noise.
- Pair with
operationalize-pql-routingto push models into automation.
