Design System
affaan-m/ECC
Generate a design system from an existing codebase or audit one for visual consistency: extract tokens (colors, typography, spacing, shadows) into design-tokens.json and CSS custom properties with…
Agent skill
Recognition Recents And Suggestions
by hashgraph-online in hashgraph-online/awesome-codex-plugins
A skill your agent uses when designing surfaces that accelerate repeat tasks through recents, frequently-used items, and contextual suggestions.
Apache-2.0Auto-check passed
Install Recognition Recents And Suggestions
$ npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins recognition-recents-and-suggestions --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions .claude/skills/recognition-recents-and-suggestions && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "recognition-recents-and-suggestions" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions into .claude/skills/recognition-recents-and-suggestions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "recognition-recents-and-suggestions", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestionsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins recognition-recents-and-suggestions --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions .agents/skills/recognition-recents-and-suggestions && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "recognition-recents-and-suggestions" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions into .agents/skills/recognition-recents-and-suggestions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "recognition-recents-and-suggestions", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins recognition-recents-and-suggestions --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions .cursor/skills/recognition-recents-and-suggestions && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "recognition-recents-and-suggestions" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions into .cursor/skills/recognition-recents-and-suggestions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "recognition-recents-and-suggestions", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/hashgraph-online/awesome-codex-plugins.git --path plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins recognition-recents-and-suggestions --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions .gemini/skills/recognition-recents-and-suggestions && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "recognition-recents-and-suggestions" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions into .gemini/skills/recognition-recents-and-suggestions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "recognition-recents-and-suggestions", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install hashgraph-online/awesome-codex-plugins recognition-recents-and-suggestionsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions .github/skills/recognition-recents-and-suggestions && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "recognition-recents-and-suggestions" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions into .github/skills/recognition-recents-and-suggestions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "recognition-recents-and-suggestions", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins recognition-recents-and-suggestions --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions .opencode/skills/recognition-recents-and-suggestions && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "recognition-recents-and-suggestions" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions into .opencode/skills/recognition-recents-and-suggestions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "recognition-recents-and-suggestions", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
recognition-recents-and-suggestions- GitHub stars
- 1.3k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 467 words
- Files
- 2 (incl. references)
- Skills in repo
- 716
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
A skill your agent uses when designing surfaces that accelerate repeat tasks through recents, frequently-used items, and contextual suggestions.
- Works in 3 steps: The "would the user pick this without… → The recents-quality audit. Sample your… → The privacy review. What do recents…
- Designing surfaces that accelerate repeat tasks through recents
- SKILL.md covers Patterns, When recents/suggestions hurt, Privacy and recents and Anti-patterns, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Recognition Recents And Suggestions is an agent skill from hashgraph-online/awesome-codex-plugins. 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.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/recents-and-prediction-cases.md`).
The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.
When your agent uses it
- Designing surfaces that accelerate repeat tasks through recents
- Frequently-used items
- Contextual suggestions
- Designing pickers used repeatedly
Example prompts
- “/recognition-recents-and-suggestions”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- 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…
- The recents-quality audit. Sample your recents lists. Are they actually relevant to current intent?
- The privacy review. What do recents reveal? Should they be hidden by default in some contexts?
What it can do on your machine
Read from SKILL.md and the folder at commit 3e1456a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are html).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Recognition Recents And Suggestions loads about 1.1k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 109 tokens; SKILL.md has 467 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its Apache-2.0 licence (© hashgraph-online). 467 words, ~1,147 tokens.
Download SKILL.mdSave it as
.claude/skills/recognition-recents-and-suggestions/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- 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.
<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
• BrowserA 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 dashboardCombine 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).
<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.
Show full SKILL.md (197 more words)Show less
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
- 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.
- The recents-quality audit. Sample your recents lists. Are they actually relevant to current intent?
- 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.
© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (references) in plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions of hashgraph-online/awesome-codex-plugins.
- SKILL.md
- references/recents-and-prediction-cases.md
Open the folder on GitHubat commit 3e1456a
Compare with similar skills
Recognition Recents And Suggestions next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Recognition Recents And Suggestions this skillhashgraph-online/awesome-codex-plugins | 1.3k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Design Systemaffaan-m/ECC | 276k | — | ~698 | Automated safety check: Pass | MIT | |
| Design Guidepaperclipai/paperclip | 100k | 1 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Design Audit Against Rams' Principlesthedotmack/claude-mem | 99k | — | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Figma Design to Codewarpdotdev/warp | 65k | 4 repos | ~2.9k | Automated safety check: Pass | AGPL-3.0 | |
| Design Consultationgarrytan/gstack | 136k | — | ~16k | Automated safety check: Notes | MIT |
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Questions about Recognition Recents And Suggestions
What does Recognition Recents And Suggestions do?
A skill your agent uses when designing surfaces that accelerate repeat tasks through recents, frequently-used items, and contextual suggestions. Recognition Recents And Suggestions is an agent skill from hashgraph-online/awesome-codex-plugins. Use this skill when designing surfaces that accelerate repeat tasks through recents, frequently-used items, and contextual suggestions.
When should I use Recognition Recents And Suggestions?
Recognition Recents And Suggestions fits situations like: designing surfaces that accelerate repeat tasks through recents; frequently-used items; contextual suggestions; designing pickers used repeatedly.
How do I install Recognition Recents And Suggestions in Claude Code?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a claude-code`. Or copy the skill folder (plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions in hashgraph-online/awesome-codex-plugins) into .claude/skills/recognition-recents-and-suggestions in your project. Claude Code loads it when a task matches its description.
How do I install Recognition Recents And Suggestions in Codex?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a codex`. Or copy the skill folder (plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/recognition-recents-and-suggestions in hashgraph-online/awesome-codex-plugins) into .agents/skills/recognition-recents-and-suggestions in your project. Codex loads it when a task matches its description.
Can I use Recognition Recents And Suggestions in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill recognition-recents-and-suggestions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/recognition-recents-and-suggestions, .gemini/skills/recognition-recents-and-suggestions, .github/skills/recognition-recents-and-suggestions and .opencode/skills/recognition-recents-and-suggestions in your project.
What does Recognition Recents And Suggestions need to run?
SKILL.md names no scripts, command-line tools or credentials: Recognition Recents And Suggestions is instructions for the agent only.
Does Recognition Recents And Suggestions access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Recognition Recents And Suggestions safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Recognition Recents And Suggestions use?
Recognition Recents And Suggestions is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Recognition Recents And Suggestions use?
About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 452 tokens, read only when the agent opens those files.
What are the alternatives to Recognition Recents And Suggestions?
Skills that share tags, products or a category with Recognition Recents And Suggestions: Design System (affaan-m/ECC, 276k stars), Design Guide (paperclipai/paperclip, 100k stars), Design Audit Against Rams' Principles (thedotmack/claude-mem, 99k stars) and Figma Design to Code (warpdotdev/warp, 65k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Recognition Recents And Suggestions?
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.