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SkillsMP a collecté 11 skills depuis opendatahub-io/agent-eval-harness. Ouvrez un skill pour examiner sa source et ses détails.
Affichage de 11 skills collectés sur 11.
Generate eval.yaml for the agent eval harness. Two modes - (1) Skill-based - examines SKILL.md, sub-skills, scripts, test cases to verify implementation quality, OR (2) Prompt-based - tests agent capabilities using custom analysis prompts (documentation…
Langue du texte source : anglais
Generate evaluation test cases for an eval.yaml. Sources cases per generation.strategy - skill analysis (default), synthetic LLM generation from generation prompts (documentation and agent-capability evals), or MLflow production traces. Bootstraps a starter…
Langue du texte source : anglais
Execute an evaluation against test cases (skill or prompt mode), score with judges, and report results. Requires eval.yaml (generated by /eval-analyze). Use when the user wants to test a skill, run eval, benchmark, compare models, detect regressions, check…
Langue du texte source : anglais
MLflow integration for evaluation — sync datasets, log run results, push/pull feedback between the harness and MLflow traces. Use when the user wants to log eval results to MLflow, sync test cases to MLflow datasets, connect judge scores to traces, pull…
Langue du texte source : anglais
Run Design-of-Experiments (DoE) evaluations with ANOVA over a matrix of agent configurations — comparing models, thinking-effort levels, prompts, or other factors across shared test cases, with repeated-measures / mixed-effects statistics that account for…
Langue du texte source : anglais
Evaluate the full harness configuration as a system. Scans all skills, commands, CLAUDE.md, and hooks for redundancy, overlap, type misclassification, and structural issues. Produces an informational report with restructuring suggestions. Use when the user…
Langue du texte source : anglais
Compare evaluation results across multiple models or runs. Takes a directory of eval run artifacts (summary.yaml, run_result.json, HTML reports) and produces a tabbed HTML comparison report with model cards, quality/cost tables, per-case breakdowns, and…
Langue du texte source : anglais
Automated skill improvement loop. Runs eval, identifies judge failures, reads traces and rationale, edits the SKILL.md to fix issues, re-runs to verify, and checks for regressions. Use when the user wants to automatically improve a skill based on eval…
Langue du texte source : anglais
Interactive review of evaluation results. Presents judge scores and skill outputs for human feedback, then proposes SKILL.md improvements based on what the user identifies. Use when the user wants to review eval results, look at results, check scores, see…
Langue du texte source : anglais
Optional environment configurator for the agent-eval-harness. Configures MLflow tracking, verifies API keys, and troubleshoots dependency issues. Detects available skills and agentic documentation (CLAUDE.md, AGENTS.md, ai-docs/) to suggest appropriate…
Langue du texte source : anglais
Query Jira for bugs in a project and summarize coverage gaps. Test fixture for e2e external-state field detection.
Langue du texte source : anglais