Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/akarachen/aghub/typesetnpx skills add AkaraChen/aghub --skill typesetgit clone --depth 1 https://github.com/AkaraChen/aghubWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/akarachen/aghub/typeset)<a href="https://agentmods.dev/skills/akarachen/aghub/typeset"><img src="https://agentmods.dev/badge/skills/akarachen/aghub/typeset.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00050 | $0.01315 |
| Opus 5 | $0.00025 | $0.00658 |
| Sonnet 5 | $0.00010 | $0.00263 |
| Haiku 4.5 | $0.00005 | $0.00131 |
Grade A, and why
typeset scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to typeset — 40 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess and improve typography that feels generic, inconsistent, or poorly structured — turning default-looking text into intentional, well-crafted type.
MANDATORY PREPARATION
Invoke /frontend-design — it contains design principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.
Assess Current Typography
Analyze what's weak or generic about the current type:
-
Font choices:
- Are we using invisible defaults? (Inter, Roboto, Arial, Open Sans, system defaults)
- Does the font match the brand personality? (A playful brand shouldn't use a corporate typeface)
- Are there too many font families? (More than 2-3 is almost always a mess)
-
Hierarchy:
- Can you tell headings from body from captions at a glance?
- Are font sizes too close together? (14px, 15px, 16px = muddy hierarchy)
- Are weight contrasts strong enough? (Medium vs Regular is barely visible)
-
Sizing & scale:
- Is there a consistent type scale, or are sizes arbitrary?
- Does body text meet minimum readability? (16px+)
- Is the sizing strategy appropriate for the context? (Fixed
remscales for app UIs; fluidclamp()for marketing/content page headings)
-
Readability:
- Are line lengths comfortable? (45-75 characters ideal)
- Is line-height appropriate for the font and context?
- Is there enough contrast between text and background?
-
Consistency:
- Are the same elements styled the same way throughout?
- Are font weights used consistently? (Not bold in one section, semibold in another for the same role)
- Is letter-spacing intentional or default everywhere?
CRITICAL: The goal isn't to make text "fancier" — it's to make it clearer, more readable, and more intentional. Good typography is invisible; bad typography is distracting.
Plan Typography Improvements
Consult the typography reference from the frontend-design skill for detailed guidance on scales, pairing, and loading strategies.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 119 lines · 50 tokens per session scan A 433fa66b0337
typeset is a skill published in the GitHub repository AkaraChen/aghub (264 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 1,315 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to typeset, differing in 40 lines, and is treated as a copy.
Other skills, from other repositories
auth-web-cloudbase
CloudBase Web Authentication Quick Guide for frontend integration after auth-tool has already been checked. Provides concise and practical Web authentication solutions with multiple login methods and complete user management.
github-skill
Work with GitHub via the gh CLI — clone repositories, create/list/merge pull requests, create/list issues, and run any other gh command (API calls, workflow runs, releases, repo administration). List operations return parsed JSON.
whatsapp-send-skill
Send WhatsApp messages to contacts, groups, or channels. Supports text, images, videos, audio, documents, stickers, locations, and contacts.
discord-user-post
Post an approved message as the logged-in Discord user through the Discord desktop app. Use for release announcements or other direct user-authored Discord posts; not for OpenClaw channel sends, bots, webhooks, relays, agent sessions, or archive search.
browse-and-evaluate
Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.
loop-engineering
Shared loop-engineering reference for COG skills - the agent loop, deterministic verifiers, termination conditions, in-loop context management, and named patterns. Invoke when designing or debugging a skill that iterates (search-verify-retry, scan-until-dry, fetch-retry-gate).