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Nw Ab Critique Dimensions Skill for Claude

Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
588
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/nWave-ai/nWave --skill nw-ab-critique-dimensions

The instruction itself

12 sections, as written by the author

Agent Quality Critique Dimensions

Use these dimensions when reviewing or validating agent definitions.

Dimension 1: Template Compliance

Does the agent follow official Claude Code format?

Check: YAML frontmatter with name and description (required) | Markdown body as system prompt | No embedded YAML config blocks | No activation-instructions or IDE-FILE-RESOLUTION sections | Skills referenced in frontmatter, not inline

Severity: High -- non-compliant agents may not load correctly.

Dimension 2: Size and Focus

Check: Core definition under 400 lines | Domain knowledge in Skills | Single clear responsibility | No monolithic sections (>50 lines without structure) | No redundant Claude default behaviors

Measurement: wc -l {agent-file}. Target: 200-400 lines.

Severity: High -- oversized agents suffer context rot.

Dimension 3: Divergence Quality

Does the agent specify only what diverges from Claude defaults?

Check: No file operation instructions | No generic quality principles ("be thorough") | No tool usage guidelines | Core principles are domain-specific and non-obvious | Each instruction justifies why Claude wouldn't do this naturally

Severity: Medium -- redundant instructions waste tokens, cause overtriggering.

Dimension 4: Safety Implementation

Check: Tools restricted via frontmatter tools field | maxTurns set | No prose-based security layers (use hooks) | No embedded enterprise safety frameworks | permissionMode set for risky actions

Severity: High -- prose safety is ineffective and token-wasteful.

Dimension 5: Language and Tone

Check: No "CRITICAL:", "MANDATORY:", "ABSOLUTE" language | Direct statements ("Do X" not "You MUST X") | Affirmative phrasing ("Do Y" not "Don't do X") | Consistent terminology | No repetitive emphasis

Severity: Medium -- aggressive language causes overtriggering on Opus 4.6.

Dimension 6: Examples Quality

Check: 3-5 canonical examples present | Cover critical/subtle decisions (not obvious cases) | Good/bad paired where useful | Concise (not full implementations)

Severity: Medium -- missing examples cause edge case failures.

Dimension 7: Skill Loading Effectiveness

Does the agent ensure skills are actually loaded during execution?

Check: Skill Loading Strategy table present for agents with 3+ skills | Every frontmatter skill has matching Load: directive in workflow | Skills path documented (~/.claude/skills/nw-{skill-name}/SKILL.md) | Phase-gated loading (not "load everything at start")

Severity: High — orphan skills (declared but never loaded) mean sub-agents operate without domain knowledge. The skills: frontmatter field is declarative only; Claude Code does not auto-load skill files.

Gold standard: nw-product-owner.md — Skill Loading Strategy table mapping phases to skills with triggers + explicit Load: directives in each workflow phase.

Dimension 8: Token Efficiency

Is the agent definition compressed without losing semantic content?

Check: No verbose prose where pipe-delimited lists suffice | Imperative voice throughout | No filler words ("in order to", "it is important to") | ### Example N: headers preserved verbatim (not inlined) | AskUserQuestion options preserved with numbered descriptions | Code blocks preserved verbatim | No duplicate content already in skills

Severity: Medium — bloated definitions waste context window and degrade performance via context rot.

Compression safe: prose descriptions, bullet lists, related items → pipe-delimited

Compression unsafe: example headers, code blocks, decision tree options, YAML frontmatter

Dimension 9: Priority Validation

Questions: 1. Is this the largest bottleneck? (Evidence required) | 2. Simpler alternatives considered? | 3. Constraint prioritization correct? | 4. Architecture data-justified?

Severity: High if agent addresses secondary concern while larger problem exists.

Review Output Format

review:
  agent: "{agent-name}"
  dimensions:
    template_compliance: {pass|fail}
    size_and_focus: {pass|fail}
    divergence_quality: {pass|fail}
    safety_implementation: {pass|fail}
    language_and_tone: {pass|fail}
    examples_quality: {pass|fail}
    skill_loading: {pass|fail|n/a}
    token_efficiency: {pass|fail}
    priority_validation: {pass|fail}
  issues:
    - dimension: "{dimension}"
      severity: "{high|medium|low}"
      finding: "{description}"
      recommendation: "{fix}"
  verdict: "{approved|revisions_needed}"

Failure Conditions

Review blocked (verdict: revisions_needed) if: any high-severity dimension fails | 3+ medium-severity fail | Agent exceeds 400 lines without Skills extraction | Zero examples provided | Agent with 3+ skills missing Skill Loading Strategy table

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How to use it

Copy the folder

Take nwave-ai/nw-ab-critique-dimensions from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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.