Claude Skill File Applies Negotiation Theory to Email Composition
A developer on r/ClaudeAI shared a SKILL.md file they built that applies negotiation theory to email composition. The skill specifically uses negotiation frameworks including BATNA (Best Alternative to a Negotiated Agreement), anchoring, and reciprocity.
How the Skill Works
The skill changes Claude's email generation approach in several specific ways:
- Before skill: Claude produces a single polite, generic email
- With skill: Claude first assesses the situation by analyzing stakes, leverage, power dynamics, and your fallback position
- The skill then generates 2-3 email variants optimized for different outcomes
- Each variant includes tradeoff analysis
Technical Implementation Details
The developer noted several key technical aspects:
- Claude knows about negotiation theory but doesn't apply it to email writing unless explicitly structured to do so
- The SKILL.md loads scenario-specific playbooks from reference files only when relevant
- This selective loading approach keeps token costs low
- The skill forces Claude to apply negotiation frameworks that it already understands conceptually
The developer mentioned being available to answer questions about how skill files work and how they structured this particular implementation.
📖 Read the full source: r/ClaudeAI
👀 See Also
Autoresearch with Claude Code on Production Codebase: 60 Experiments, 3 Changes Kept
A developer ran 60 iterations of autoresearch with Claude Code on a production hybrid search system (Django, pgvector, Cohere embeddings), keeping only 3 changes with a 93% failure rate. The process identified ineffective optimizations and caught a Redis caching bug.
OpenClaw hands-on experience: setup, skills, and cost realities
A developer tested OpenClaw for building a family assistant, finding it can create folder structures, modify configs, write Python scripts, and organize files directly. The experience required WSL on Windows, OpenAI API keys with credits, additional tooling for web browsing, and careful management of different communication channels.
Localizing Large Codebases with LLMs: A Developer's Workflow for 4,500 UI Keys
A developer shares their workflow for localizing a game with 4,500 UI keys using LLMs. They found that adding context to translation prompts and using local models like Qwen 3 8B produced acceptable quality, while cloud models like Claude and Gemini Pro struggled with file size and accuracy.
Using Markdown Files as Workflow Engine for Claude Code in Kubernetes
A developer replaced traditional pipeline tools like Dagster or Prefect with plain English markdown files that Claude Code executes as a Kubernetes CronJob. The system coordinates steps by writing artifacts to disk and has been running for over a month.