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- Agent Harness Architect
Works with the AI Agents you already use
Agent Harness Architect
Same model, wildly different results depending on the harness.
$24
Agent Harness Architect
Example session with this skill installed
I have a support agent that uses a SQL tool and a Knowledge Base tool. It keeps trying to write SQL for general questions and gets stuck when the database returns no results. Fix it.
- Read your context and instructions
- Compiled the agent harness architect
I've architected a new harness. The system prompt now includes a strict 'Method' section defining when to use the KB vs SQL. I added a 'Failure & Escalation' protocol for empty SQL results and a Harness Map moving schema enforcement from the prompt to your tool definitions.
Connects securely to your tools. The creator never sees your data.
About this skill
The difference between an agent that works and one that flails is the harness — the scaffolding around the model: the system prompt, the tool definitions, context management, guardrails, and the feedback loop. Same model, wildly different results depending on the harness. And the most-neglected piece is the one at the center: the system prompt itself, which teams grow by accretion until it's a contradictory wall of text the model half-follows. Agent Harness and System Prompt Architect designs that core. Describe the agent's job, its tools, and its constraints, and it writes a structured system prompt — role and objective, capabilities with when-and-when-not-to-use-each-tool guidance, boundaries that separate hard nevers from confirm-before-acting, a method, a precise output contract, and defined failure and escalation behavior — written so every instruction is specific, testable, priority-ordered, and free of the contradictions that make models drop rules at random. Then it maps the whole harness: which concerns the prompt should own versus what belongs in tool definitions, context management, guardrails and hooks, or evaluations — because a hard limit stated in prose is a hope, not a control, and format belongs in the output contract, not buried in a paragraph. The download includes three reference files: a system-prompt structure guide, a harness component map, and a worked sample that turns a misbehaving refund agent into a structured harness. It designs the harness and writes the instructions from what you describe — it doesn't run the agent or test the prompt against a model, so pair it with an evaluation to confirm behavior. Works with Claude Code, Cursor, Codex CLI, Gemini CLI, and any SKILL.md agent.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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