Skill Bundles

    Read the source. Install what you trust.

    Each skill bundle packages a reusable agent behavior: a prompt, supporting files, and evaluation criteria. Browse the public catalog, review the full source, then install a private copy you can edit and experiment with.

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    109 published bundles ready to inspect and install

    Skill bundlev1.0.0

    Baseline Agent Benchmarking

    Measure current agent performance on the target workflow before RL intervention

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    RL Feasibility Assessment

    Determine whether a workflow is actually amenable to RL improvement (clear rewards, sufficient volume, safe to explore)

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    Workflow Audit

    Map an enterprise workflow end-to-end: inputs, decisions, tools, outputs, success criteria

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    Model Versioning For RL

    Track and switch between reference model, current policy, and reward model versions during training

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    VLLM For RL

    Configure vLLM or similar engines for RL workloads (batched generation, multiple completions)

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    High Throughput Rollout Serving

    Serve models at high throughput for RL rollout collection (not just user-facing latency)

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    70/100 quality
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    Skill bundlev1.0.0

    Compute Budgeting For RL

    Estimate and optimize GPU hours needed for RL training runs

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    Checkpoint Selection

    Choose the best model checkpoint based on eval performance, not just training metrics

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    70/100 quality
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    Skill bundlev1.0.0

    Training Stability Debugging

    Diagnose and fix common RL training failures: reward collapse, mode collapse, KL explosion

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    Kl Divergence Management

    Control how far the policy drifts from the reference model during training

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    Reward Model Training

    Train reward models from human preference data, handle label noise and distribution shift

    0 installs
    70/100 quality
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    Skill bundlev1.0.0

    RL Hyperparameter Tuning

    Tune learning rates, KL penalties, reward scaling, batch sizes for RL stability

    0 installs
    70/100 quality
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