Work Item Sequencing
forcedotcom/salesforcedx-vscode
Numbering convention for ordering GUS work items within an epic.
A skill your agent uses whenever the user must hold a sequence of items in working memory — phone numbers, OTP codes, account IDs, address strings, multi-step instructions, long forms, navigation…
$ npx skills add hashgraph-online/awesome-codex-plugins --skill chunking -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins chunking --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/chunking .claude/skills/chunking && 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 "chunking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking into .claude/skills/chunking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chunking", 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/chunkingType 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 chunking -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins chunking --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/chunking .agents/skills/chunking && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "chunking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking into .agents/skills/chunking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chunking", 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 chunking -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins chunking --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/chunking .cursor/skills/chunking && 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 "chunking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking into .cursor/skills/chunking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chunking", 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/chunking--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 chunking -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins chunking --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/chunking .gemini/skills/chunking && 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 "chunking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking into .gemini/skills/chunking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chunking", 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 chunkingInstalls 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 chunking -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/chunking .github/skills/chunking && 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 "chunking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking into .github/skills/chunking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chunking", 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 chunking -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 chunking --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/chunking .opencode/skills/chunking && 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 "chunking" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking into .opencode/skills/chunking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chunking", 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.
chunkingA skill your agent uses whenever the user must hold a sequence of items in working memory — phone numbers, OTP codes, account IDs, address strings, multi-step instructions, long forms, navigation…
Chunking is an agent skill from hashgraph-online/awesome-codex-plugins. Use this skill whenever the user must hold a sequence of items in working memory — phone numbers, OTP codes, account IDs, address strings, multi-step instructions, long forms, navigation menus with many items. Trigger when designing OTP / verification UIs, formatting numeric strings, breaking long forms into sections, grouping nav items, or reviewing surfaces that "have too many things at once." Chunking is one of the foundational principles in 'Universal Principles of Design' (Lidwell, Holden, Butler 2003)…
Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/working-memory-research.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.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 78497e5. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Chunking loads about 3.2k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 144 tokens; SKILL.md has 1,507 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.
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.
The full file from hashgraph-online/awesome-codex-plugins at commit 78497e5, republished under its Apache-2.0 licence (© hashgraph-online). 1,507 words, ~3,179 tokens.
.claude/skills/chunking/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Chunking is the practice of grouping a long string of items into a smaller number of meaningful units, each containing a few items. The classic insight: working memory can hold only a handful of independent items, but each "item" can itself be a chunk containing several pieces. Phone numbers are easier to remember as 555-867-5309 (three chunks) than as 5558675309 (ten digits). The same principle applies broadly across UI design.
Working memory is a small, short-lived store for the items the user is actively manipulating. Its capacity is roughly four to seven independent units. When information is presented as one long unbroken sequence, the user has to hold all of it as separate units and quickly hits the limit. When information is grouped into a few meaningful chunks, the same total content fits within the working-memory budget. Chunking is the design technique for fitting information to that budget.
When users must hold multiple items in mind — to dial a phone number, type a confirmation code, follow multi-step directions, complete a multi-part form — the amount they can hold determines whether they succeed. Exceeding working memory means they make mistakes, look back, or give up.
Chunking expands the effective capacity by packing more information into each chunk. A user can hold roughly 4 chunks; if each chunk contains 3 digits, that's 12 digits total — meaningful for phone numbers. Without chunking, 12 raw digits is well past the limit.
Chunking also accelerates learning: chunked patterns become familiar units (the "555" prefix becomes one chunk, not three) and free up capacity for new information.
The book's specific warning: don't chunk reference content the user scans rather than memorizes.
The discriminator: are users holding the items in mind (apply chunking) or finding them (don't)?
Different sources give different numbers; the working consensus:
These are heuristics; specific tasks may justify different sizes. The grouping should always be perceptually clear (visual gap, dash, slot separation).
Most common chunking case. A 10-digit US phone number formatted three ways:
5558675309 ← unchunked: 10 digits, hard to verify or recall
555-867-5309 ← three chunks: 3-3-4
(555) 867-5309 ← same three chunks, with area code marked
555 867 5309 ← spaces instead of dashesThe chunked versions are easier to read aloud, easier to verify, easier to remember briefly. Most international phone formats follow similar logic.
A 6-digit OTP entered into a single field is hard to verify mid-entry. Chunked input fields make each digit's position visible:
<input type="text" inputmode="numeric" maxlength="6" /> <!-- unchunked -->
<!-- vs. chunked input -->
<div class="otp-input" role="group" aria-label="Verification code">
<input type="text" inputmode="numeric" maxlength="1" />
<input type="text" inputmode="numeric" maxlength="1" />
<input type="text" inputmode="numeric" maxlength="1" />
<span class="separator" aria-hidden>—</span>
<input type="text" inputmode="numeric" maxlength="1" />
<input type="text" inputmode="numeric" maxlength="1" />
<input type="text" inputmode="numeric" maxlength="1" />
</div>The chunked version (3-3) helps users verify they typed the right digits and matches the chunked format that's typically displayed in the originating email or SMS.
A 24-field signup form is overwhelming. Group into 4 sections of ~6 fields each, with named headings:
<form>
<section>
<h2>Account</h2>
<!-- 5 fields: email, password, name, etc. -->
</section>
<section>
<h2>Profile</h2>
<!-- 4 fields: title, bio, photo, etc. -->
</section>
<section>
<h2>Workspace</h2>
<!-- 6 fields: workspace name, members, etc. -->
</section>
<section>
<h2>Preferences</h2>
<!-- 5 fields: notifications, language, etc. -->
</section>
</form>The user holds in mind "I'm in the workspace section" rather than "I'm at field 17 of 24." Each section is a manageable chunk.
A sidebar with 18 nav items is hard to scan; grouped into 3 themed sections of 6 items each:
<nav>
<h3>Workspace</h3>
<ul>
<li><a href="/dashboard">Dashboard</a></li>
<li><a href="/projects">Projects</a></li>
<li><a href="/team">Team</a></li>
<li><a href="/calendar">Calendar</a></li>
<li><a href="/files">Files</a></li>
<li><a href="/inbox">Inbox</a></li>
</ul>
<h3>Reports</h3>
<ul>...</ul>
<h3>Settings</h3>
<ul>...</ul>
</nav>Users learn the section structure quickly and use it to predict where things live.
An address string is a chunked structure even when displayed compactly:
1234 Main Street, Apt 5B
San Francisco, CA 94110Two-line break separates "street" chunk from "city/state/zip" chunk. The internal commas chunk apartment from street and city from state from zip. Users parse and recall this far better than the same characters in one continuous line.
"To set up your account: Open Settings, click Notifications, choose Email, set frequency, save changes" — five steps in one sentence. Chunked as a numbered list:
1. Open Settings
2. Click Notifications
3. Choose Email
4. Set frequency
5. Save changesEasier to follow; users can mark progress and look back at any step.
Western music notation chunks notes into measures (typically 3 or 4 beats). Beats group into bars; bars group into phrases; phrases group into sections. Musicians read music as nested chunks, not as individual notes.
Skilled readers don't process individual letters; they process chunks (common letter combinations, then whole words, then phrases). Speed reading techniques are largely about recognizing larger chunks more efficiently.
Expert chess players recall positions vastly better than novices — not because their working memory is larger, but because they chunk pieces into meaningful patterns (a defensive formation, an opening structure). De Groot's classic studies (1965) showed that experts and novices recalled random piece arrangements equally; the expert advantage came entirely from recognizing meaningful chunks.
Area codes are mnemonic chunks that group geography into recognizable units. "212" is Manhattan; "415" is San Francisco. The numeric chunk doubles as a categorical signal.
performance-load — chunking is the canonical reduction of cognitive load.hicks-law — fewer visible options means faster decisions; chunking and Hick's Law often combine in nav design.progressive-disclosure — disclosure works between chunks (show one section, hide others); chunking works within the visible content.mnemonic-device — chunking is itself a mnemonic technique; explicit mnemonics layer on top.signal-to-noise-ratio (perception) — well-chunked content has less perceptual noise.proximity (perception) — proximity is the visual mechanism for showing chunks: closer items group, gaps mark boundaries.hierarchy (perception) — chunked content carries a hierarchy of structure (sections > items).chunking-form-grouping — applying chunking to long forms.chunking-numeric-and-otp — applying chunking to numeric strings, OTP codes, and identifiers.Chunking is the cheapest cognitive lift available in design — it costs only structure, not new content. The discipline is recognizing when content is being held in working memory (chunk it) versus scanned for retrieval (don't add chunks; use search). When applied correctly, chunking turns "too much to hold" into "manageable."
© 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
SKILL.md and 1 other file (references) in plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking of hashgraph-online/awesome-codex-plugins.
Open the folder on GitHubat commit 78497e5
Chunking 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 |
|---|---|---|---|---|---|---|
| Chunking this skillhashgraph-online/awesome-codex-plugins | 1.2k | — | ~3.2k | Automated safety check: Pass | Apache-2.0 | |
| Work Item Sequencingforcedotcom/salesforcedx-vscode | 1k | — | ~1.1k | Automated safety check: Pass | BSD-3-Clause | |
| Action Items List Managerasgeirtj/system_prompts_leaks | 69k | — | ~4.9k | Automated safety check: Pass | CC0-1.0 | |
| Legal Holdanthropics/claude-for-legal | 9.6k | 1 repos | ~3.8k | Automated safety check: Pass | Apache-2.0 | |
| Document To Action ItemsNousResearch/hermes-agent | 252k | — | ~976 | Automated safety check: Pass | MIT | |
| Meeting Action ItemsNousResearch/hermes-agent | 252k | — | ~950 | Automated safety check: Pass | MIT |
forcedotcom/salesforcedx-vscode
Numbering convention for ordering GUS work items within an epic.
asgeirtj/system_prompts_leaks
Maintains a private to-do list stored as a JSON file in the assistant's notes: adding tasks, recording what is awaited, tracking blockers and closing finished items.
anthropics/claude-for-legal
Issue, refresh, release, or report on legal holds — drafts the hold notice as .docx, updates legalhold fields in log.yaml, and calendars the next refresh.
NousResearch/hermes-agent
Extract cited obligations, deadlines, tasks from documents. An agent skill from NousResearch/hermes-agent.
NousResearch/hermes-agent
Turn meeting notes into cited decisions, owners, tickets. An agent skill from NousResearch/hermes-agent.
vellum-ai/vellum-assistant
Create and manage automated email drip sequences. An agent skill from vellum-ai/vellum-assistant.
hashgraph-online/awesome-codex-plugins
Create original anime-style reaction stickers as looping GIFs and MP4 previews, using generated character pose sheets and timed key poses.
hashgraph-online/awesome-codex-plugins
Manage and query Calibre libraries with the calibredb CLI (local paths or Calibre Content server URLs).
hashgraph-online/awesome-codex-plugins
A skill your agent uses when adding, changing, testing, or debugging Rust HTTP APIs and services, especially when Codex needs black-box integration tests, random-port app startup, real database test…
hashgraph-online/awesome-codex-plugins
Make a studio's game look like something at build time — a cover from a real frame of the game (free), painted covers, backdrops, textures and character plates from image models through the…
hashgraph-online/awesome-codex-plugins
Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.
hashgraph-online/awesome-codex-plugins
Analyze nonfiction manuscripts for reader engagement signals, including heading-level word counts, slow starts, long slogs, weak takeaway titles, value pacing, beta-reader comment dropoff, and…
A skill your agent uses whenever the user must hold a sequence of items in working memory — phone numbers, OTP codes, account IDs, address strings, multi-step instructions, long forms, navigation…. Chunking is an agent skill from hashgraph-online/awesome-codex-plugins. Use this skill whenever the user must hold a sequence of items in working memory — phone numbers, OTP codes, account IDs, address strings, multi-step instructions, long forms, navigation menus with many items.
Chunking fits situations like: the user must hold a sequence of items in working memory — phone numbers; address strings; multi-step instructions; navigation menus with many items.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill chunking -a claude-code`. Or copy the skill folder (plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking in hashgraph-online/awesome-codex-plugins) into .claude/skills/chunking in your project. Claude Code loads it when a task matches its description.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill chunking -a codex`. Or copy the skill folder (plugins/HDeibler/universal-design-principles/plugins/cognition-and-learnability-principles/skills/chunking in hashgraph-online/awesome-codex-plugins) into .agents/skills/chunking in your project. Codex loads it when a task matches its description.
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 chunking -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chunking, .gemini/skills/chunking, .github/skills/chunking and .opencode/skills/chunking in your project.
SKILL.md names no scripts, command-line tools or credentials: Chunking is instructions for the agent only.
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.
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.
Chunking 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.
About 3.2k tokens (SKILL.md is roughly 13k 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 1.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Chunking: Work Item Sequencing (forcedotcom/salesforcedx-vscode, 1k stars), Action Items List Manager (asgeirtj/system_prompts_leaks, 69k stars), Legal Hold (anthropics/claude-for-legal, 9.6k stars) and Document To Action Items (NousResearch/hermes-agent, 252k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,242 GitHub stars. The repository holds 686 skills in this directory. The repository was last updated on October 8, 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.