messaging-framework

31 stars 7 forks
28
D

Use to structure value propositions, proof points, and objection responses for enablement assets.

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Also in: github api

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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skilz install gtmagents/gtm-agents/messaging-framework
skilz install gtmagents/gtm-agents/messaging-framework --agent opencode
skilz install gtmagents/gtm-agents/messaging-framework --agent codex
skilz install gtmagents/gtm-agents/messaging-framework --agent gemini

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Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/gtmagents/gtm-agents
2. Copy the agent skill directory:
cp -r gtm-agents/plugins/sales-enablement/skills/messaging-framework ~/.claude/skills/

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Related Agentic Skills

Agentic Skill Details

Repository
gtm-agents
Stars
31
Forks
7
Type
Non-Technical
Meta-Domain
development
Primary Domain
javascript
Market Score
28

Agent Skill Grade

D
Score: 67/100 Click to see breakdown

Score Breakdown

Spec Compliance
11/15
PDA Architecture
18/30
Ease of Use
17/25
Writing Style
7/10
Utility
12/20
Modifiers: +2

Areas to Improve

  • Description needs trigger phrases
  • Missing Reference Files for Templates
  • Framework Lacks Procedural Steps

Recommendations

  • Address 2 high-severity issues first
  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 2026-01-24

Developer Feedback

I've been looking at how you structured the messaging framework layer, and I'm curious about the trade-offs you made between keeping it abstract enough for different segments while still providing enough concrete guidance—at a 67/100, there's solid foundational work here, but the skill could punch harder with some tightening up around how templates and procedures actually get executed.

Links:

The TL;DR

You're at 67/100, D territory. This is graded against Anthropic's skill quality standards. Your strongest area is Spec Compliance (11/15)—the YAML structure is clean and the terminology is consistent. Weakest is Progressive Disclosure Architecture (18/30)—mostly because the templates you mention aren't actually provided as separate reference files, which kills both discoverability and token efficiency.

What's Working Well

  • Consistent terminology across the entire skill (value pillars, proof points, objection handling)—makes it easy to follow your mental model
  • Clear "When to Use" section that actually tells people when to invoke this (structure value props, handle objections, build talk tracks)
  • Solid YAML frontmatter with valid metadata and proper naming conventions (hyphen-case, appropriate description length)
  • Logical flow from audience definition through objection mapping—the conceptual arc makes sense

The Big One: Templates Aren't Templated

You mention three critical templates—"Message house worksheet", "Objection/response matrix", "Story library index"—but they only exist as bullet points. This is a missed opportunity. Create actual reference files (references/message-house-worksheet.md, references/objection-response-matrix.md, `references/story-...

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