ios-log-diagnose

ios-log-diagnose is a Runtime diagnostics & profiling skill for AI agents, published by UniClipboard in the UniClipboard repository on GitHub. Skillspace rates ios-log-diagnose D (68/100) and it passed the safety scan; the rating is based on static analysis only.

Drive the UniClipboard iOS app in a simulator and read its OSLog yourself to diagnose a mobile-sync bug, instead of asking the user to paste logs. Use when debugging why the iOS sync engine or M5 reducer did something, reproducing an iOS sync / clipboard bug on the simulator, or whenever you'd otherwise ask the user "what do the logs say". All output is Swift OSLog under subsystem `app.uniclipboard` — the Rust core (uc-mobile) emits no logs of its own; the Swift shell logs the reducer's decisions.

Grade
D
Quality
68 / 100
Safety
Passed
GitHub stars
1,712

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubUniClipboard/UniClipboard

Our review

Architecture
100 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
Not declared. Check the repository before reusing it.

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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