Skill Quality Report: onboarding-cro

Evaluation Time: 2026-04-15
Evaluation Mode: Item-by-item review

Overall Score

Level guide:

• 90-100: Excellent - ready to use
• 70-89: Good - small but meaningful room to improve
• 50-69: Fair - needs important revisions
• <50: Not qualified - requires substantial rewrite

Skill Strengths

1. [Effectiveness] Trigger intent is concrete and retrieval-friendly - Evidence: description explicitly lists realistic phrases such as users sign up but don't use the product, low activation rate, and time to value.
2. [Effectiveness] Context-first assessment reduces redundant discovery - Evidence: If .agents/product-marketing-context.md exists ... read it before asking questions.
3. [Effectiveness] The flow includes operational outputs, not only principles - Evidence: required output includes Onboarding Audit, Step-by-step flow, Empty state copy, and Metrics plan.
4. [Safety] It defines scope boundaries with related-skill routing - Evidence: For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

Skill Improvement Areas

1. [Standards] Frontmatter governance metadata is incomplete - Evidence: available header fields mainly expose name, description, and version; Impact: weaker maintainability for version ownership, licensing, and machine indexing consistency.
2. [Effectiveness] Verification criteria are implied but not explicit - Evidence: the skill asks for audits and plans, but does not define a pass/fail validation checklist for recommendation quality; Impact: two agents may produce inconsistent depth and quality for the same input.
3. [Conciseness] Main prompt body is long for frequent runtime loading - Evidence: long inlined tables and pattern catalogs are all in the main file, while only experiment details are delegated to references; Impact: higher token cost and slower turnaround in long sessions.

Insights

1. Pairing trigger keyword lists with explicit business pain signals improves activation of the right skill. - Application: CRO and growth diagnosis skills.
2. Requiring output artifacts (audit, flow, metrics) keeps strategy discussions operational. - Application: consulting-style skills that must produce implementation-ready deliverables.
3. Related-skill routing is a practical way to prevent scope drift in adjacent growth tasks. - Application: skill suites where onboarding, signup, and lifecycle channels overlap.

Issue List

[Medium] Standards - Missing governance metadata

• Location: frontmatter
• Description: missing structured governance fields such as author, license, and richer machine-readable metadata blocks.
• Suggestion: complete metadata fields and standardize retrieval tags across the repository.

[Medium] Effectiveness - No explicit quality gate for recommendations

• Location: output section and workflow instructions
• Description: expected outputs are specified, but there is no explicit validation rubric to verify recommendation quality before final response.
• Suggestion: add a short quality gate (for example, “must include quantified impact hypothesis and priority rationale per issue”).

[Low] Conciseness - Progressive disclosure can be stronger

• Location: main SKILL body
• Description: high-volume reference-like content is kept inline.
• Suggestion: move stable catalogs (for example, product-type patterns) into references/ and keep the main file focused on trigger, decision logic, and output contract.

Prioritized Recommendations

1. [Must] Add complete governance metadata for better maintainability and indexing.
2. [Should] Add an explicit quality gate to standardize recommendation depth and consistency.
3. [Could] Increase progressive disclosure to reduce token load during runtime.