output-eval-validate-judge
Validate LLM judges against human labels using TPR/TNR metrics and train/dev/test splits. Use after writing a judge prompt to verify it agrees with human judgment.
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Validate LLM judges against human labels using TPR/TNR metrics and train/dev/test splits. Use after writing a judge prompt to verify it agrees with human judgment.
Use when the user asks to create, build, generate, scaffold, or plan a new workflow. Orchestrates the full planning process including architecture, steps, prompts, evaluators, and testing strategy using specialized subagents.
Guide to the providerOptions structure in .prompt files — decision tree for where an option goes, common mistakes, per-provider quick reference, and Anthropic prompt caching. Use when writing or reviewing .prompt file frontmatter (provider, model, providerOptions, messageOptions).
Create, edit, convert, or audit ChatLuna sub-agent markdown files. Use when adding a new sub-agent, refining a sub-agent prompt, choosing a sub-agent's goal and output contract, restricting tools, skills, MCP, or computer permissions, pinning or omitting a model, setting maxTurns, placing agents under local `data/chatluna/agents`, writing them into a remote sandbox before `agentcli sync`, or converting Claude or OpenCode agent files into ChatLuna-compatible sub-agents.
Apply a Claude Fable 5 inspired operating style inside Codex. Use when the user asks to make Codex act like Fable, Fable5, fablize, or Value-for-Fable/VFF; convert Anthropic or Claude system-prompt/tool instructions to Codex; set up a Fable-style tool-first workflow with goal gates, investigation, verification grounding, cost-aware routing, or 2-pass review; create Codex AGENTS.md guidance from Fable-like behavior; or connect Codex to an authorized Fable-compatible provider through an OpenAI-compatible gateway.
Bootstrap skill — establishes how to find and use GodotPrompter skills, with platform-specific tool mapping
Core Smart Ralph skill defining common arguments, execution modes, and shared behaviors across all Ralph plugins.
Audit and remediate Entroly's MCP marketplace quality with evidence, adversarial validation, and no score gaming.