harness-integration-guide

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Reference guide for building new Omnigent harness integrations — covers SDK/subprocess harnesses and native harnesses as separate tracks, each with their own feature matrix, implementation patterns, and prioritized checklist.

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Skill Content

# Harness integration guide This skill describes the **feature matrix** every Omnigent harness must consider. Use it when planning, reviewing, or implementing a new harness. Omnigent has two distinct harness tracks with different architectures and feature sets: - **SDK/subprocess harnesses** — run the vendor model directly (in-process SDK, CLI subprocess, or ACP subprocess). They own the model lifecycle. - **Native harnesses** — wrap a vendor's own TUI or server and mirror its output into Omnigent. They observe and relay, rather than drive. --- ## Part 1 — SDK / subprocess harnesses These harnesses run the vendor model directly and bridge Omnigent tools into the vendor's tool-calling interface. ### Capability matrix | Capability | What it means | |---|---| | **Connects to Omnigent MCP** | Harness exposes/consumes tools via the MCP protocol (in-proc SDK MCP server) | | **Model override** | User can select a model via `--model` / config; some harnesses are vendor-locked (e.g. Claude-only, GPT-only, Gemini-only) | | **Auth** | How credentials are obtained — API key, gateway token, vendor CLI login, OAuth, etc. | | **Streaming** | Harness forwards token-level or delta-level streaming to the Omnigent forwarder | | **Omnigent policies** | Harness enforces Omnigent-side tool policies — must support ALLOW, ASK, and DENY verdicts for both tool calls and tool results | | **Native elicitation** | When a policy verdict is ASK, the harness surfaces the approval request in the ...

Details

Author
omnigent-ai
Repository
omnigent-ai/omnigent
Created
1 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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