harness-model-protocollisted

# Harness-Model Protocol Analysis Analyzes the interface layer between agent frameworks (harness) and language models. This skill examines the **wire protocol**, **message encoding**, and **agentic primitives** that enable tool-augmented conversation. ## Distinction from tool-interface-analysis | tool-interface-analysis | harness-model-protocol | |------------------------|------------------------| | How tools are registered and discovered | How tool calls are encoded on the wire | | Schema generation (Pydantic → JSON Schema) | Schema transmission to LLM API | | Error feedback patterns | Response parsing and error extraction | | Retry mechanisms at tool level | Streaming mechanics and partial responses | | Tool execution orchestration | Message format translation | ## Process 1. **Map message protocol** — Identify wire format (OpenAI, Anthropic, custom) 2. **Trace tool call encoding** — How tool calls are requested and parsed 3. **Analyze streaming mechanics** — SSE, WebSocket, chunk handling 4. **Catalog agentic primitives** — System prompts, scratchpads, interrupts 5. **Evaluate provider abstraction** — How multi-LLM support is achieved ## Message Protocol Analysis ### Wire Format Families **OpenAI-Compatible (Chat Completions)** ```python { "model": "gpt-4", "messages": [ {"role": "system", "content": "..."}, {"role": "user", "content": "..."}, {"role": "assistant", "content": "...", "tool_calls": [...]}, {"role": "tool", "too