Detect new commits and closed issues, then re-run evaluations and update reports.
npx skills add https://github.com/brazil-bench/pourpoise --skill re-evaluate
Please help me install this Agent Skill. Skill: re-evaluate Source: https://github.com/brazil-bench/pourpoise/tree/main/skills/re-evaluate Command: npx skills add https://github.com/brazil-bench/pourpoise --skill re-evaluate
Re-evaluate an evaluation of an attempt repository after issues are closed and changes are detected, updating reports and surfacing regressions.
Use the re-evaluate skill to re-check a specific attempt, for example: re-evaluate 2025-12-13-python-claude-hive
High-intent search queries and answers about installing and using this skill.
To re-evaluate pytest results after closing GitHub issues, this tool automatically pulls new commits via Git, re-runs relevant evaluations, updates the main report, and files any new regression issues using the GitHub CLI.
Automated attempt re-evaluation is the process of detecting new commits and closed issues in a repository, re-running pytest evaluations, updating the main report, and filing regressions to keep results current after changes.
Yes, re-evaluating an attempt repository requires the GitHub CLI and Git to pull changes and detect closed issues, alongside pytest to execute the actual test evaluations and update reports.
You can automatically file regression issues after re-running pytest evaluations by using this tool to detect new commits, execute the tests, and create or update issues via the GitHub CLI based on the latest results.
Yes, you can update an existing evaluation report by re-evaluating the attempt, which detects new commits, re-runs the relevant pytest evaluations, and applies the updated results directly to the main report.
davpatel605-beepConfigures GitHub authentication via tokens, SSH keys, or gh CLI for git and API workflows.
kunalrawat425Aggregate type checks, linting, tests, and dead-code detection into a weighted 0-10 health score.
richardnguyen0715Manage GitHub issues from the command line using gh or git tools.
CodeAtCodeAutomate Python testing workflows with pytest fixtures and parametrization.
