edge-case-hunter
SkillDev toolsFocuses specifically on unusual inputs, boundary conditions, empty states, and unexpected user behavior that implementations commonly miss. Use to find what a normal test pass would skip over.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the edge-case-hunter skill
What this skill tells your AI
The instructions your AI receives, as published by codebygarv/ai-skills in skills/testing/edge-case-hunter/SKILL.md and read by ahel’s review.
Purpose
Enumerate the edge cases a given piece of functionality is likely to mishandle — unusual input, boundary values, empty/missing states, and unexpected user behavior — the class of case that a "does it work for the normal case" pass typically skips.
When to Use
- Before shipping something that handles user input or external data.
- After writing normal-case tests, to find what's still missing.
- Specifically want edge cases enumerated, separate from a general bug hunt (see Bug Hunter for defects in existing code; this skill is about enumerating cases to consider, whether or not code exists yet).
What to Analyze
- Boundary values — zero, negative, empty string/array/object, exactly at a limit (min/max), one below/above a limit.
- Empty & missing states — no data yet (first-time user), data deleted mid-session, a required relationship missing (e.g. a comment whose author was deleted).
- Unexpected user behavior — double-submitting a form, navigating away mid-action, using browser back/forward against app state, extremely fast repeated actions.
- Unusual but valid input — very long strings, unicode/emoji, whitespace-only input, numbers as strings, timezone edge cases (midnight, DST transitions, leap years/seconds).
- Concurrent/simultaneous actions — two actors acting on the same resource at once, the same actor acting on two devices/tabs at once.
- Degraded conditions — slow network, partial data load, a dependency being down or timing out.
Output Format
- A checklist grouped by category (Boundary Values, Empty/Missing States, Unexpected Behavior, Unusual Input, Concurrency, Degraded Conditions).
- Each item: the specific case, why it's plausible (not just theoretically possible), and what currently happens (if known/inferable) or what should happen.
- Prioritize cases realistic for this specific feature over generic edge cases that don't actually apply to it.
Avoid
- Generating a generic checklist that doesn't reflect what this specific feature actually does — every case should be plausible for the feature at hand.
- Treating truly impossible cases (violating a hard invariant enforced elsewhere) as if they need handling here too.
- Listing a case without saying why it matters or what should happen — a bare list of scenarios isn't actionable.
Signals
- GitHub stars
- 25
- Forks
- 1
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
edge-case-hunter- Source
- github.com/codebygarv/ai-skills