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Skill evidence / onboarding-optimization
Skill profile

onboarding-optimization

When the user wants to improve their app's onboarding experience.

What this skill does for you

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.

Quoted from the skill description in the pinned source

Who made it

Publisherappeeky
Repositoryaso-skills
Installs2,300as of Sep 27, 2026

Use it with Edge

Bring this skill into your Edge workflow. Read the pinned instructions to check its setup.

Use it with EdgeRead skill source

Security evidence

3 static scans, 0 counted findings. What this means: the listed scanners recorded the results shown for this package revision.

ScannerDateResultFindings
Edge static checks2026-09-27Pass0
Cisco skill-scanner2026-09-27Pass0
Semgrep Edge rules2026-09-27Pass0

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 4df730f456c21e42b9a2ea2be89fb32caf787728. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 4df730f456c21e42b9a2ea2be89fb32caf787728. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 4df730f456c21e42b9a2ea2be89fb32caf787728. Raw findings: . Counted findings: .

Source and licence

Repository
https://github.com/appeeky/aso-skills
Pinned skill file
View source at revision
Revision
4df730f456c21e42b9a2ea2be89fb32caf787728
Package hash
sha256:8cf366a04c60e05d6e9e1d01152b240bf9b2b3b10d074f38088d44f6625a145b
Licence
MIT