Detailed review process, v2 validation checklist, and scoring methodology for agent definition reviews
npx skills add https://github.com/nWave-ai/nWave --skill nw-review-workflow
Run against every agent under review. Each item pass/fail.
--- delimited YAML with name and description10. Consistent terminology: One term per concept
11. Clear delegation: Description states when to delegate
For each of 7 critique dimensions (from critique-dimensions skill):
IF any high-severity dimension fails:
verdict = "revisions_needed"
ELIF count(medium-severity failures) >= 3:
verdict = "revisions_needed"
ELSE:
verdict = "approved"
High-severity: template_compliance, size_and_focus, safety_implementation, priority_validation
Medium-severity: divergence_quality, language_and_tone, examples_quality
Every finding includes: Dimension (which of 7) | Severity (high/medium/low) | Finding (observed, with line numbers/counts) | Recommendation (specific fix action)
| Residual Pattern | What to Flag |
|-----------------|-------------|
| Embedded YAML config blocks | Should be frontmatter or removed |
| activation-instructions section | Remove -- Claude Code handles activation |
| IDE-FILE-RESOLUTION section | Remove -- not needed in v2 |
| commands with 10+ entries | Reduce to 3-5 focused |
| Inline embed_knowledge | Extract to Skills |
| 5+ "production frameworks" | Remove -- platform handles safety |
| CRITICAL: prefixed instructions | Rephrase as calm direct statements |
| Python/YAML safety code examples | Remove -- aspirational, not executable |
revisions_needed, include prioritized fix listAdditional checks for nWave command files (tasks):
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take nwave-ai/nw-review-workflow from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.