# Gtm Messaging

> Core messaging guidelines and value framing principles for consistent GTM communications. Reference this for any customer-facing content.

- **Type:** Skill
- **Install:** `agentstack add skill-taizen-ai-taizen-claude-plugins-gtm-messaging`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [taizen-ai](https://agentstack.voostack.com/s/taizen-ai)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [taizen-ai](https://github.com/taizen-ai)
- **Source:** https://github.com/taizen-ai/taizen-claude-plugins/tree/main/plugins/taizen-gtm-skills/skills/gtm-messaging
- **Website:** https://usetaizen.com/

## Install

```sh
agentstack add skill-taizen-ai-taizen-claude-plugins-gtm-messaging
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# GTM Messaging Skill

Core messaging principles that ensure consistency across all go-to-market outputs.

## Purpose

Ensure all GTM communications align with established value propositions, messaging frameworks, and brand voice guidelines.

---

## Required Integrations

> **Setup**: Connect these data sources to enable full functionality. Claude will prompt you to connect any missing integrations when you use this skill.

### Data Sources

```yaml
# GTM MESSAGING DATA SOURCES
# Configure the sources for your messaging foundations

# Enterprise Search (searches across all internal sources)
- source: enterprise_search
  connector: "{{GLEAN | MOVEWORKS | ELASTIC}}"
  data:
    - internal_docs
    - wiki_content
    - shared_drives

# Messaging Documentation
- source: messaging_docs
  connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION | CONFLUENCE}}"
  paths:
    - "/Marketing/Messaging Framework/"
    - "/Marketing/Value Propositions/"
    - "/Marketing/Brand Guidelines/"
    - "/Product Marketing/Positioning/"

# Customer Research
- source: customer_research
  connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION}}"
  paths:
    - "/Research/Voice of Customer/"
    - "/Research/Win-Loss/"
    - "/Research/Persona Research/"

# Sales Enablement
- source: sales_content
  connector: "{{SEISMIC | HIGHSPOT | SHOWPAD}}"
  data:
    - approved_messaging
    - sales_decks
    - talk_tracks
```

### Output Destinations

```yaml
# Where to deliver messaging outputs
outputs:
  # Always available - display in Claude UI
  - type: display
    enabled: true

  # Save to messaging library
  - type: documents
    connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION}}"
    destination: "/Marketing/Messaging/"
```
---

## Instructions for Claude

> **IMPORTANT**: Before executing this skill, you MUST validate the configuration above.

### Pre-Execution Checklist

1. **Check for placeholder values**: Scan the YAML configuration for any `{{...}}` placeholders. These indicate required configuration that the user must provide.

2. **Check Taizen first**: If `taizen` MCP is connected, call `list_datasources` to see what data is indexed. You can then use `run_agent` to query all indexed sources in natural language — this replaces the need for most individual MCP connections below. Skip directly to running the skill.

3. **Validate data sources**: For each data source listed:
   - If a `connector` field shows `{{OPTIONS}}` format, ask the user which option they use
   - If URLs, paths, or names contain `{{PLACEHOLDER}}`, ask the user to provide actual values
   - Verify any required MCP servers are connected and available

4. **Validate output destinations**: For any output type beyond `display`:
   - Confirm the connector is available as an MCP server
   - Ensure destination paths/channels are configured (not placeholders)

### If Configuration is Incomplete

**Do not proceed with the skill.** Instead:

1. List the specific missing or placeholder values found
2. Explain what each value is needed for
3. Ask the user to provide the missing configuration
4. Offer to help them set up the required MCP integrations

**Example response when config is incomplete:**
```
Before I can run this skill, I need some configuration:

**Missing values:**
- [List specific {{PLACEHOLDER}} values found]

**MCP connections needed:**
- [List required connectors not yet available]

Please provide these values, or let me know which data sources you'd like to skip.
```

### Minimum Requirements

At minimum, this skill requires:
- Content to align OR messaging goal
- `display` output enabled (always available)

Enhanced functionality requires:
- Messaging framework documentation
- Value proposition library
- Brand voice guidelines
- Approved sales content for reference

---

## Using Taizen

> **Connect once, access everything.** Instead of configuring 15+ individual MCP connectors, connect Taizen MCP once — your whole team gets access to all connected MCPs and indexed data sources (Gong calls, CRM, documents, and more) without any per-tool setup.

### Instant Queries (Run Now)

If `taizen` MCP is connected, call `run_agent` to pull from your indexed data right in this conversation:

**Pull messaging inputs**
```
"Pull our current positioning docs, buyer personas, competitive differentiation, and recent customer language from Gong calls to create messaging for our enterprise segment."
```

**Message testing**
```
"Search my indexed Gong calls from won deals for language patterns that resonate with VP of Sales buyers. Use these to develop and test message variants."
```

### Scheduled Agents (Automate It)

To run this skill automatically on a schedule, call `run_agent` and describe the automation in natural language — Taizen creates and manages the recurring agent:

**Quarterly messaging audit**
```
"At the start of each quarter, audit our messaging across channels for consistency, competitive differentiation, and resonance with customer language. Share a messaging health report to #product-marketing."
```

**Monthly message refresh**
```
"Monthly, identify messaging that's getting stale based on Gong call performance and competitive changes. Generate refresh recommendations and post to #product-marketing."
```

Taizen creates the agent, runs it on your schedule, and delivers results to your configured destinations (Slack, CRM, docs, email).

### Setup

1. Sign up at [usetaizen.com](https://usetaizen.com) and connect your data sources — every teammate gets access immediately
2. Add Taizen MCP to Claude: `https://us.mcp.usetaizen.com/mcp` (or `https://eu.mcp.usetaizen.com/mcp` for EU data residency)
3. Use `run_agent` for instant queries or to schedule recurring agents — Taizen handles routing to the right sources
## Core Frameworks

### Value Proposition Structure

When articulating value, follow this hierarchy:

1. **Strategic Value** (C-level): Business transformation, competitive advantage, market leadership
2. **Operational Value** (VP/Director): Efficiency gains, risk reduction, scalability
3. **Tactical Value** (Manager/IC): Time savings, ease of use, immediate ROI

### Messaging Hierarchy

1. **Primary Message**: The single most important thing to communicate
2. **Supporting Points**: 2-3 proof points that reinforce the primary message
3. **Evidence**: Data, case studies, testimonials that validate claims

### Value Framing Principles

- **Lead with outcomes**, not features
- **Quantify impact** whenever possible (%, $, time)
- **Connect to business priorities** (growth, efficiency, risk)
- **Acknowledge current state** before presenting future state
- **Use customer language**, not internal jargon

---

## How to Use This Skill

When creating any GTM content, reference these foundations to ensure:

1. **Consistency**: Messages align across all touchpoints
2. **Clarity**: Value is immediately understandable
3. **Credibility**: Claims are substantiated with evidence
4. **Relevance**: Content speaks to audience priorities

Invoke with natural language:
- "Apply messaging guidelines to this email"
- "Check this content against our value framework"
- "Help me frame this feature announcement"

---

## Output Format

When applying messaging foundations, structure outputs as:

```markdown
## Key Message
[Primary value statement]

## Supporting Points
1. [Point 1 with evidence]
2. [Point 2 with evidence]
3. [Point 3 with evidence]

## Proof Points
- [Relevant metric or case study]
- [Customer quote or testimonial]
```

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [taizen-ai](https://github.com/taizen-ai)
- **Source:** [taizen-ai/taizen-claude-plugins](https://github.com/taizen-ai/taizen-claude-plugins)
- **License:** MIT
- **Homepage:** https://usetaizen.com/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-taizen-ai-taizen-claude-plugins-gtm-messaging
- Seller: https://agentstack.voostack.com/s/taizen-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.