pql-framework
Methodology for defining product-qualified lead (PQL) signals, scoring, and routing.
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Installation for Agentic Skill
View all platforms →skilz install gtmagents/gtm-agents/pql-framework skilz install gtmagents/gtm-agents/pql-framework --agent opencode skilz install gtmagents/gtm-agents/pql-framework --agent codex skilz install gtmagents/gtm-agents/pql-framework --agent gemini
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Agentic Skill Details
- Repository
- gtm-agents
- Type
- Non-Technical
- Meta-Domain
- development
- Primary Domain
- github
- Market Score
- 28.6
Agent Skill Grade
D
Score: 65/100
Click to see breakdown
Score Breakdown
Areas to Improve
- No trigger phrases
- Templates are mentioned but not provided as reference files; user cannot act on the skill without these
- Description lacks specific trigger terms that users would naturally search for
Recommendations
- Focus on improving Utility (currently 11/20)
- Address 2 high-severity issues first
- Add trigger phrases to description for discoverability
Graded: 1/24/2026
Developer Feedback
I've been looking at your pql-framework skill, and I'm curious about the decision to abstract query language primitives the way you have—most frameworks I see either go full DSL or stick with string building, but you're threading something in between.
Links:
The TL;DR
You're at 65/100, which puts you in D territory. This skill addresses a real PLG problem—defining and scoring product-qualified leads—but it's currently too conceptual. Your strongest area is Writing Style (8/10), which means the prose is clean and professional. The weakest area by far is Utility (11/20)—templates are mentioned but not provided, and there are no concrete examples or validation patterns developers can actually implement.
What's Working Well
- Clear conceptual structure. The 5-step framework (Signal Library → Scoring Model → Routing Logic → Integration → Measurement Loop) is sound and easy to follow.
- Consistent terminology. PQL/PQA language is used cleanly throughout without unnecessary jargon.
- Professional tone. The writing is straightforward and objective—no marketing fluff, which is refreshing.
The Big One: Missing Templates and Examples
This is the issue holding you back the most. You mention "Signal inventory worksheet," "Scoring matrix with weights and decay logic," and "Routing decision tree," but none of these templates actually exist. A developer reading your skill knows conceptually what a PQL program should include, but they can't execute it without seeing actual templates.
Fix: Create three reference files:
references/signal-inventory-template.md– Sample signals with point values (e.g., "Invited 3+ users (5 pts), Hit workspace limit (8 pts)")references/scoring-matrix-template.md– Actual scoring table with decay rules and thresholdsreferences/routing-decision-tree.md– Decision logic linking tiers to specific plays
This alone would add 7 points and make the skill actually useful.
Other Things Worth Fixing
Add trigger phrases to your description. Right now it's "Methodology for defining product-qualified lead signals..." Users search for "score leads," "PQL program," "qualify accounts." Update the description to include these terms for discoverability (+2 points).
No validation checklist. The Measurement Loop step mentions tracking conversion but doesn't explain how to validate your scoring model actually works. Add a
references/validation-checklist.mdwith steps like: run on historical cohort → compare against actual conversions → identify false positives → adjust weights (+3 points).Vague sub-steps in the framework. "Weight signals, set decay rules" is clear at 50,000 feet but lacks the decision points someone new to PQL would need (e.g., "1-10 point scale?" "30-day or event-based decay?"). Add a bit more tactical detail here.
Quick Wins
- Add three reference template files (biggest bang for buck)
- Strengthen the description with specific trigger phrases
- Create a validation checklist so users know how to verify their implementation
- Expand framework steps with concrete decision points
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