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onboarding-optimization

When the user wants to improve their app's onboarding experience, increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow. Use when the user mentions "onboarding", "first-run", "activation", "tutorial", "day 1 retention", "new user flow", "permission prompts", "sign-up conversion", "onboarding funnel", or "users dropping off early". For overall retention strategy, see retention-optimization. For paywall placement, see monetization-strategy.

68

Quality

81%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-crafted, token-efficient instruction skill: dense actionable heuristics, clear audit workflow, and concrete output templates. The main gaps are the undefined screen-scoring scale in Step 2 and the absence of any post-recommendation verification step.

Suggestions

Define the scoring scale in the Step 2 table (e.g., score each factor 0-2 and give the decision rule for when a screen is removed, deferred, or kept).

Add a validation checkpoint after the audit output, such as 'confirm each recommended change against the drop-off data gathered in the Initial Assessment before presenting the revised flow'.

Consider moving the funnel benchmark and app-type pattern tables into a references/ file to keep SKILL.md as a lean overview.

DimensionReasoningScore

Conciseness

The body is lean and dense — tables and compact flow diagrams carry domain-specific heuristics (benchmarks, permission timing, conversion rates) that Claude cannot be assumed to know, with no re-explanation of familiar concepts. Every section earns its place.

5 / 5

Actionability

Guidance is concrete and specific (permission timing table, sign-up friction patterns with recommendations, output-format templates), but the Step 2 'Score Each Screen' table leaves the Score column empty and defines only '0 = skip it', so the actual per-factor scoring scale is undefined.

4 / 5

Workflow Clarity

A clear sequence runs from Initial Assessment (baseline gathering) through Audit Steps 1-4 to pattern selection and a defined output format. Checkpoints exist up front, but there are no downstream validation or verification steps (e.g., confirming recommendations against funnel data), which the top anchor expects.

4 / 5

Progressive Disclosure

No bundle files exist, and the ~190-line body is well organized into clearly signaled sections with one-level cross-skill references. Benchmark tables and app-type patterns are arguably large enough to split into reference files, so content placement is good but not fully split.

4 / 5

Total

17

/

20

Passed

Description

81%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with excellent trigger-term coverage and explicit scope boundaries. Its main weakness is that the 'what' is expressed as user goals and metric outcomes rather than distinct concrete capabilities, leaving the skill's actual actions implicit.

Suggestions

State the skill's concrete actions directly in third person (e.g., 'Audits the first-run flow, times permission prompts, and redesigns sign-up friction') in addition to the user-goal framing.

Fold the activation-metric variations (activation rate, Day 1 drop-off) into one clause and use the freed space to name 1-2 distinct deliverables, such as the onboarding audit output.

DimensionReasoningScore

Specificity

The description names the domain and several concrete outcomes ('increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow'), but these are variations of a single aim framed as user goals rather than a list of distinct capabilities the skill performs (e.g., audit flow, redesign permission timing).

3 / 5

Completeness

Both what and when are present, with an excellent explicit 'Use when...' clause listing concrete trigger phrases. The 'what' is framed as user goals ('When the user wants to improve...') rather than a direct statement of the skill's actions, so it is slightly less explicit than the top anchor.

4 / 5

Trigger Term Quality

Comprehensive coverage of natural trigger phrasings users would actually say: 'onboarding', 'first-run', 'activation', 'tutorial', 'day 1 retention', 'new user flow', 'permission prompts', 'sign-up conversion', 'onboarding funnel', and the colloquial 'users dropping off early'.

5 / 5

Distinctiveness Conflict Risk

Clear niche (first-run/activation) with explicit boundary disambiguation ('For overall retention strategy, see retention-optimization. For paywall placement, see monetization-strategy.'), minimizing risk of triggering the wrong skill.

5 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Eronred/aso-skills
Reviewed

Table of Contents

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