recognition-recents-and-suggestions
/recognition-recents-and-suggestions
Pomaga projektować listy ostatnio używanych elementów, często wybieranych pozycji i podpowiedzi kontekstowych, które przyspieszają powtarzalne zadania i oszczędzają ponowne wpisywanie.
- Autor
- Deibler ↗
- Repozytorium
- universal-design-principles ↗
- Licencja
- MIT
- Ostatnia zmiana repozytorium
- 03.05.2026
Ocena i bezpieczeństwo
- Pliki w paczce
- 2
- Skrypty
- 0
- Komentarze HTML
- 1
- Adresy URL w SKILL.md
- 0
Brak sygnałów. Repozytorium zmienione 03.05.2026, bez odwołań do wycofanych modeli i API.
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Co robi i kiedy
Pomaga projektować listy ostatnio używanych elementów, często wybieranych pozycji i podpowiedzi kontekstowych, które przyspieszają powtarzalne zadania i oszczędzają ponowne wpisywanie.
Oryginalny opis (EN)
Use this skill when designing surfaces that accelerate repeat tasks through recents, frequently-used items, and contextual suggestions. Trigger when designing pickers used repeatedly, command palettes, navigation that should adapt to user behavior, or any surface where a returning user shouldn''t have to retype their frequent destinations. Sub-aspect of `recognition-over-recall`; read that first.
Jak działa
- Patterns
- When recents/suggestions hurt
- Privacy and recents
- Anti-patterns
- Heuristics
- Related sub-skills
Podgląd SKILL.md
---
name: recognition-recents-and-suggestions
description: 'Use this skill when designing surfaces that accelerate repeat tasks through recents, frequently-used items, and contextual suggestions. Trigger when designing pickers used repeatedly, command palettes, navigation that should adapt to user behavior, or any surface where a returning user shouldn''t have to retype their frequent destinations. Sub-aspect of `recognition-over-recall`; read that first.'
---
# Recents, frequents, and contextual suggestions
Recognition is fastest when the user doesn't even have to scan a long list — when the system anticipates and surfaces the likely options first. Recents, frequents, and predictive suggestions all leverage this: the user's likely target is at the top, often without typing anything.
## Patterns
### Recents
A list of items the user has recently interacted with. Surfaced at the top of pickers, navigation, or empty search inputs.
```html
<combobox label="Recipient">
<input placeholder="Search recipients..." />
<listbox>
<group label="Recent">
<option>Maria Mendoza (last sent: yesterday)</option>
<option>Marketing Team (last sent: 3 days ago)</option>
</group>
<group label="All">...</group>
</listbox>
</combobox>
```
Most users compose for a small set of recipients repeatedly; recents collapse the recall task.
### Frequents
Items used most often (regardless of recency). Useful when usage is clustered around a small set but not necessarily recent.
```
Frequently used apps:
• Email
• Slack
• Code editor
• Browser
```
A common laptop dock pattern.
### Recommended / suggested
System-predicted likely options based on context. Examples:
- A "for you" feed.
- "People you may know."
- "Suggested replies" in messaging.
- "Suggested tags" when categorizing.
Recommendations work when the prediction is good. Bad recommendations (irrelevant, wrong) are worse than none — they distract and erode trust.
### Pinned / favorites
User-curated frequently-accessed items. Less algorithmic than recents/suggestions; user-explicit.
```
Pinned:
★ Q4 Planning Doc
★ Team OKRs
★ Customer feedback dashboard
```
Combine with recents and suggestions for a complete fast-access surface.
### Smart defaults
Pre-fill fields with predicted values based on context (signed-in user, recent inputs, time of day, location).
```html
<form>
<label>Country
<select name="country">
<option value="US" selected>United States</option>
<!-- selected because of user's IP location -->
</select>
</label>
</form>
```
The user can change but rarely needs to.
## When recents/suggestions hurt
- **When the prediction is bad.** Wrong recents distract; the user has to filter past them.
- **When privacy matters.** Recents reveal user history; in shared-device contexts this can leak information.
- **When the option set is critical to the task.** A "recent" suggestion in a destructive action might bias the user toward the wrong choice.
For high-stakes actions, present the full set without privileging recents.
## Privacy and recents
Recents reveal user activity to anyone with screen access. Considerations:
- **Don't surface recents on shared/public devices** unless explicitly opted in.
- **Provide a "clear recents" option.**
- **Don't leak across tenants** (a recent in workspace A shouldn't appear when the user switches to workspace B).
- **Be cautious with sensitive contexts** (health apps, finance apps, dating apps).
## Anti-patterns
- **Stale recents** that include items the user no longer cares about, never expiring.
- **Recents that span privacy boundaries** (work email recents in personal context).
- **Suggestions that don't update** as the user's behavior changes.
- **Surfacing recents in wrong contexts** (showing "recent files" on a different user's account).
## Heuristics
1. **The "would the user pick this without typing?" check.** For each picker, ask: in the median case, can the user get to their target without typing? If yes, recents are doing their job.
2. **The recents-quality audit.** Sample your recents lists. Are they actually relevant to current intent?
3. **The privacy review.** What do recents reveal? Should they be hidden by default in some contexts?
## Related sub-skills
- **`recognition-over-recall`** (parent).
- **`recognition-pickers-and-palettes`** — picker patterns recents augment.
- **`satisficing`** — recents enable satisficing by surfacing acceptable options first.
- **`hicks-law-defaults`** — defaults and recents both reduce decision cost.
Pliki w paczce (2)
- SKILL.md 5 KB
- references/recents-and-prediction-cases.md 2 KB
Wersje
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