backlog-moderator
Business moderator for backlog prioritization debates. Synthesizes Champion and Critic views into final rankings. Optimizes for team productivity and sustainable velocity.
Browse published AI skills maintained by pcortes. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
34Repository stars across indexed skills
0Repository forks
0Average repository stars per indexed skill
0Repository stars may repeat across skills from the same repository.
Business moderator for backlog prioritization debates. Synthesizes Champion and Critic views into final rankings. Optimizes for team productivity and sustainable velocity.
Generate GitHub issues from an approved engineering specification. Use to break down a spec into implementable, atomic tasks with dependencies, sizing, and labels.
Coordinates adaptive QA testing across behavioral, contract, and regression dimensions. Routes to specialized sub-agents based on context and depth.
Estimate issue complexity before implementation to prevent timeouts. Uses cheap estimation to save expensive implementation tokens.
Research external libraries with evidence-backed responses and GitHub permalinks. Use when investigating library APIs, implementation patterns, or historical context for open source dependencies.
Implementation Agent: Full TDD workflow in a single context window. Writes tests, implements code, and iterates until all tests pass.
Reproduce bugs and gather evidence for root cause analysis. Use when investigating a bug report to confirm reproduction and collect detailed information about the failure.
Analyze reproduction evidence to identify the root cause of bugs. Use after reproduction to trace execution and find the exact location and reason for the failure.
Analyzes code diffs to identify affected endpoints and prioritize regression testing. Focuses QA effort on changed areas.
Draft detailed engineering specs from an approved PRD. Use when generating or updating the engineering specification for a feature, before implementation begins.
Generate GitHub issues from an approved engineering specification. Use to break down a spec into implementable, atomic tasks with dependencies, sizing, and labels.
Design fix plans based on root cause analysis. Use after root cause is identified to plan specific code changes and test cases needed to fix the bug.
Analyze implementation failures and generate recovery plans. Use when an issue fails and needs diagnosis for retry or escalation.
Implementation Agent: Full TDD workflow in a single context window. Writes tests, implements code, and iterates until all tests pass.
Apply critic feedback to improve an engineering spec. Use when revising a spec based on review comments to address issues and improve quality scores.
Analyze test failures and suggest fixes for Feature Swarm verification. Use when tests fail during the verification phase to diagnose root cause and determine if automatic recovery is possible.
Draft detailed engineering specs from an approved PRD. Use when generating or updating the engineering specification for a feature, before implementation begins.
Analyze reproduction evidence to identify the root cause of bugs. Use after reproduction to trace execution and find the exact location and reason for the failure.
Engineering critic for backlog prioritization debates. Challenges proposed rankings with feasibility concerns, hidden complexity, and realistic effort estimates.
Analyzes code changes for quality issues, code smells, SOLID violations, LLM-generated code problems, and refactoring opportunities. Reports findings with severity, evidence, and suggested fixes.
Design fix plans based on root cause analysis. Use after root cause is identified to plan specific code changes and test cases needed to fix the bug.
Split complex issues into smaller, implementable sub-issues. Called automatically when ComplexityGate determines an issue needs splitting.
Review and score engineering specs against a quality rubric. Use when evaluating a spec draft before implementation to ensure it meets quality standards and identifies potential issues.
Reviews code quality analyst findings. Validates issues are real, severity is appropriate, and suggested refactorings are practical.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.