Structured AI debate templates and synthesis. Use when orchestrating multi-round debates between AI tools, 'debate topic', 'argue about', 'stress test idea', 'devil advocate'.

Use when user asks to "discover tasks", "find next task", "prioritize issues", "what should I work on", or "list open issues". Discovers and ranks tasks from GitHub, GitLab, local files, and custom sources.

Use when the user asks about plan drift, reality check, comparing docs to code, project state analysis, roadmap alignment, implementation gaps, or needs guidance on identifying discrepancies between documented plans and actual implementation state.

Use when improving CLAUDE.md or AGENTS.md project memory files.

Use when checking cross-file consistency: tools vs frontmatter, agent references, duplicate rules, contradictions.

Use when improving documentation structure, accuracy, and RAG readiness.

Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.

Use when analyzing plugin structures, MCP tools, and plugin security patterns.

Use when improving general prompts for structure, examples, and constraints.

Use when reviewing SKILL.md files for structure and trigger quality.

Use when preparing releases, validating cross-platform compatibility, or updating installation infrastructure. Meta-skill for maintaining AgentSys's 3-platform architecture.

Adding a new skill to the project. Skills follow the **Agent Skills Open Standard** (agentskills.io).

Use when user asks to "deep review the code", "thorough code review", "multi-pass review", or when orchestrating the Phase 9 review loop. Provides review pass definitions (code quality, security, performance, test coverage), signal detection patterns, and iteration algorithms.

Use when synthesizing perf findings into evidence-backed recommendations and decisions.

Use when managing perf baselines, consolidating results, or comparing versions. Ensures one baseline JSON per version.

Use when running performance benchmarks, establishing baselines, or validating regressions with sequential runs. Enforces 60s minimum runs (30s only for binary search) and no parallel benchmarks.

Use when mapping code paths, entrypoints, and likely hot files before profiling.

Use when appending structured perf investigation notes and evidence.

Use when profiling CPU/memory hot paths, generating flame graphs, or capturing JFR/perf evidence.

Use when generating performance hypotheses backed by git history and code evidence.