An agent harness is everything around the model inside an AI agent. The model itself only generates text. The harness runs it in a loop, gives it tools and executes its tool calls, assembles context, stores memory, enforces limits and decides when to stop. An agent's quality depends on the harness as much as on the model: the same LLM behaves differently in different harnesses.
A harness usually includes:
- The loop: model, tool call, result
- A system prompt and skills with instructions
- Context assembly and memory
- Step and time limits, error handling
- Access permissions and human approval for actions
Claude Code, Codex and Cursor are examples of agents with a ready-made harness: you just connect tools and skills.
For work in a team chat app, Pachca gives agents ready-made parts of the harness: Pachca CLI with commands for API methods, Agent Skills with instructions and workflows, llms.txt and the OpenAPI spec. There's no need to build an integration from scratch: the agent learns what Pachca can do from these tools.
Learn more in the Help center
Read the article →For developers
Docs on dev.pachca.com →