# Internal Comms Anthropic

> To write internal communications, use this skill for:

- Skill: `techwavedev/internal-comms-anthropic` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add techwavedev/internal-comms-anthropic`
- Raw SKILL.md: https://api.skillmd.com/api/skills/techwavedev/internal-comms-anthropic/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: techwavedev (https://skillmd.com/u/techwavedev)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/techwavedev/internal-comms-anthropic

---


## When to use this skill
To write internal communications, use this skill for:
- 3P updates (Progress, Plans, Problems)
- Company newsletters
- FAQ responses
- Status reports
- Leadership updates
- Project updates
- Incident reports

## How to use this skill

To write any internal communication:

1. **Identify the communication type** from the request
2. **Load the appropriate guideline file** from the `examples/` directory:
    - `examples/3p-updates.md` - For Progress/Plans/Problems team updates
    - `examples/company-newsletter.md` - For company-wide newsletters
    - `examples/faq-answers.md` - For answering frequently asked questions
    - `examples/general-comms.md` - For anything else that doesn't explicitly match one of the above
3. **Follow the specific instructions** in that file for formatting, tone, and content gathering

If the communication type doesn't match any existing guideline, ask for clarification or more context about the desired format.

## Keywords
3P updates, company newsletter, company comms, weekly update, faqs, common questions, updates, internal comms

---

<!-- AGI-INTEGRATION-START -->

## AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)

### Memory-First Protocol

Retrieve prior agent configurations, team compositions, and orchestration patterns. Critical for multi-agent system consistency.

```bash
# Check for prior AI agent orchestration context before starting
python3 execution/memory_manager.py auto --query "agent patterns and orchestration strategies for Internal Comms Anthropic"
```

### Storing Results

After completing work, store AI agent orchestration decisions for future sessions:

```bash
python3 execution/memory_manager.py store \
  --content "Agent pattern: hierarchical orchestration with Control Tower dispatcher, 3 specialist sub-agents" \
  --type decision --project <project> \
  --tags internal-comms-anthropic ai-agents
```

### Multi-Agent Collaboration

This skill is inherently multi-agent. Use cross-agent context to coordinate task distribution and avoid duplicate work.

```bash
python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Agent architecture designed — Control Tower + specialist agents with shared Qdrant memory" \
  --project <project>
```

### Control Tower Integration

Register agents and tasks with the Control Tower (`execution/control_tower.py`) for centralized orchestration across machines and LLM providers.

### Blockchain Identity

Each agent has a cryptographic Ed25519 identity. All memory writes are signed — enabling trust verification in multi-agent systems.

<!-- AGI-INTEGRATION-END -->