Run skill eval cases and generate pass/fail scorecards with Haiku 4.5 subagents.
npx skills add https://github.com/rajitsaha/100xprism --skill eval-rajitsaha
Please help me install this Agent Skill. Skill: eval Source: https://github.com/rajitsaha/100xprism/tree/main/modules/eval Command: npx skills add https://github.com/rajitsaha/100xprism --skill eval-rajitsaha
This Skill eliminates the manual, error-prone work of verifying whether your AI skills still trigger correctly and produce expected outputs after updates or changes, preventing broken or underperforming skills from being used in production workflows.
Use the eval skill to run all evals for the recently updated copywriting skill and generate a full pass/fail scorecard.
High-intent search queries and answers about installing and using this skill.
Regression testing on AI skills uses automated eval grading to verify trigger accuracy and output quality after code changes. It fans out parallel Haiku 4.5 subagents to grade each assertion and generates a deterministic pass/fail scorecard.
AI skill evaluation is the process of validating trigger accuracy and output quality before production release. Assertion grading works by deploying Haiku 4.5 subagents to evaluate each eval case and produce structured pass/fail scorecards.
Preventing overlapping skill triggers requires trigger overlap linting to detect skills that would fire on each other's prompts. This runs before assertion grading to reduce false positives and ensure accurate scorecard generation.
Automated eval scoring supports pre-release quality validation for AI coding tools including Claude Code, Cursor, and Copilot. It requires the eval-harness.py script to perform structural validation and render pass/fail scorecards.
Validating AI skill quality without manual review is best achieved through automated eval grading using Haiku 4.5 subagents. This approach provides deterministic pass/fail results for trigger accuracy and output assertions across all eval cases.
An eval harness script like eval-harness.py is needed for skill quality validation to perform structural validation and render scorecards. It orchestrates parallel Haiku 4.5 subagents to grade assertions and produce deterministic pass/fail results.
zhengfranCreate and iteratively improve Claude Code skills with SKILL.md drafts and eval runs.
picmakproDiagnose root causes of bugs and document verified fixes.
rudironsoniGenerate AI coding tool configurations from a unified rule set.
romiluz13Audit Claude Code configurations and generate a 0–100 score with fixes.
