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    8 skills found

    Claude Code Agent Harness Setup

    by Shogun Labs

    $15

    Project-specific Claude Code agent harness setup

    1
    securityquality-gategitleaks+3

    Enterprise Multi Agent Automation — Production Harness with Denbun, Retry & Self Healing

    by Shogun Labs

    Free

    Battle-tested orchestration framework for running 3+ Claude Code agents in parallel. Covers task routing, denbun handoff protocol, exponential-backoff retry, rate-limit guards, structured JSON logging, and automated self-healing — patterns from real production deployments.

    1
    8 5.0
    multi-agentorchestrationclaude-code+3

    evaluating ai harness dimensions

    by loreto

    $10

    Evaluates AI coding agent platforms across five structural dimensions that determine real-world performance independently of model quality, so teams select on architectural fit rather than benchmark scores.

    3
    agent-architectureai-agentsai-coding-agents+12

    harness engineering

    by Roy Yuen

    $8

    Design, debug, and harden AI control loops with explicit contracts and automated verification harnesses.

    2
    2
    ai-agentsdevopsllm-ops+3

    agent eval harness

    by Echo Rose

    $5

    "Agent Eval Harness - A premium AI agent skill"

    1
    ai-agentdeveloper-toolsai-agents+4

    Agent Harness Architect

    by PubsProToolkit

    $14

    Model quality is table stakes — the harness is where agents win or fail. This designs yours: it writes a structured, testable system prompt (role, tools, boundaries, method, output contract, failure handling) and maps every concern to the right layer — prompt, tool, guardrail, or evaluation — so the pieces reinforce each other instead of fighting.

    1
    agent-harnesssystem-promptai-agents+6

    agent harness builder

    by Echo Rose

    $5

    Agent Harness Builder - AI agent skill

    1
    ai-agentdeveloper-toolsai-agents+4

    benchmarking ai agents beyond models

    by loreto

    Free

    Published AI benchmarks measure brains in jars. They test models in isolation or within a single reference harness — and then attribute all performance to the model. This skill teaches you to decompose agent performance into its two actual components: model capability and harness multiplier. The result is evaluations that predict real-world behavior instead of benchmark theater.

    1
    14 5.0
    agent-evaluationai-agentsai-benchmarking+10