lms-front: Skill for Claude Code

.agents/skills/harden/SKILL.md

harden is a skill for Claude Code, Codex from guillermoscript/lms-front. It costs 32 tokens per session (2,178 once invoked), scanned A, a copy of harden, MIT.

A skill for making user interfaces handle difficult real-world conditions, including long text, empty data, unusual characters, many items, network failures, validation errors, and different languages or writing directions.

In plain words
What is it for?
Use it to harden interfaces against text overflow, errors, offline or slow networks, permission failures, rate limits, internationalization, large numbers, and edge-case input.
Why use it?
It finds problems that are hidden when an interface is tested only with short, complete, English-language data and successful requests. The goal is to keep the interface usable when inputs, translations, or services behave unexpectedly.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument; installed under .agents/ (shared by several agents).

This is guillermoscript/lms-front's own configuration. It tells Claude Code and Codex how to work on lms-front itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything lms-front configures →

Reuse

Borrowing it

Nothing to install: this file belongs to guillermoscript/lms-front. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/guillermoscript/lms-front/master/.agents/skills/harden/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/guillermoscript/lms-front

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for harden

README.md
[![agentmods](https://agentmods.dev/badge/skills/guillermoscript/lms-front/harden/github.svg)](https://agentmods.dev/skills/guillermoscript/lms-front/harden)
Your own site
<a href="https://agentmods.dev/skills/guillermoscript/lms-front/harden"><img src="https://agentmods.dev/badge/skills/guillermoscript/lms-front/harden/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for harden

Your own site · 80×15
<a href="https://agentmods.dev/skills/guillermoscript/lms-front/harden"><img src="https://agentmods.dev/badge/skills/guillermoscript/lms-front/harden.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,178 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.02178
Opus 5.5 $0.00013 $0.00871
Sonnet 5.5 $0.00006 $0.00436
Haiku 4.5 $0.00003 $0.00218

Measured 1mo ago against content hash 6114cdc92bd9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

harden 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 1mo 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.

Origin

This is a copy

92% identical to harden — 11 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.

.agents/skills/harden/SKILL.md · 357 lines

How it starts

The opening of the file, as written. The whole thing — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Strengthen interfaces against edge cases, errors, internationalization issues, and real-world usage scenarios that break idealized designs.

Assess Hardening Needs

Identify weaknesses and edge cases:

  1. Test with extreme inputs:

    • Very long text (names, descriptions, titles)
    • Very short text (empty, single character)
    • Special characters (emoji, RTL text, accents)
    • Large numbers (millions, billions)
    • Many items (1000+ list items, 50+ options)
    • No data (empty states)
  2. Test error scenarios:

    • Network failures (offline, slow, timeout)
    • API errors (400, 401, 403, 404, 500)
    • Validation errors
    • Permission errors
    • Rate limiting
    • Concurrent operations
  3. Test internationalization:

    • Long translations (German is often 30% longer than English)
    • RTL languages (Arabic, Hebrew)
    • Character sets (Chinese, Japanese, Korean, emoji)
    • Date/time formats
    • Number formats (1,000 vs 1.000)
    • Currency symbols

CRITICAL: Designs that only work with perfect data aren't production-ready. Harden against reality.

Hardening Dimensions

Systematically improve resilience:

Text Overflow & Wrapping

Long text handling:

/* Single line with ellipsis */
.truncate {
  overflow: hidden;
  text-overflow: ellipsis;
  white-space: nowrap;
}

/* Multi-line with clamp */
.line-clamp {
  display: -webkit-box;
  -webkit-line-clamp: 3;
  -webkit-box-orient: vertical;
  overflow: hidden;
}

/* Allow wrapping */
.wrap {
  word-wrap: break-word;
  overflow-wrap: break-word;
  hyphens: auto;
}

Flex/Grid overflow:

/* Prevent flex items from overflowing */
.flex-item {
  min-width: 0; /* Allow shrinking below content size */
  overflow: hidden;
}

/* Prevent grid items from overflowing */
.grid-item {
  min-width: 0;
  min-height: 0;
}

Responsive text sizing:

  • Use clamp() for fluid typography
  • Set minimum readable sizes (14px on mobile)
  • Test text scaling (zoom to 200%)
  • Ensure containers expand with text

Read the full file on GitHub · 357 lines

Changes

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.

  1. 1mo ago First seen · 357 lines · 32 tokens per session scan A 6114cdc92bd9

Subscribe to this mod's changes

harden is a skill published in the GitHub repository guillermoscript/lms-front (40 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 2,178 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to harden, differing in 11 lines, and is treated as a copy.

Related

Other skills, from other repositories

apple-design

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading)…

classroomio/classroomio · 80 tokens

stage-and-commit

Stage changed files and create a commit following the repo's translation, formatting, and git workflow rules. Use when the user asks to stage, commit, or both.

classroomio/classroomio · 38 tokens

maintaining-modding-environments

Use after first-run for ongoing modpack maintenance: update/install KB packs, author or register custom/mod KB packs, maintain localization glossary KBs for translator use, prune KB cache, health-check the environment, version-pin KB/tooling, or handle recurring BGS modding environment care.

hashgraph-online/awesome-codex-plugins · 65 tokens

using-bgs-translator

A translation workflow for Bethesda Game Studios plugins, which are game modification files such as .esp, .esm, and .esl. It prepares the plugin text for AI translation and exports files that xTranslator can use.

hashgraph-online/awesome-codex-plugins · 94 tokens

fastgpt-docker-deploy

FastGPT Docker Compose self-hosting deployment workflow. Use when a user asks an AI agent to deploy FastGPT with Docker by referencing /deploy/SKILL.md, including creating an empty fastgpt directory, running the install script in non-interactive mode, starting Docker Compose, monitoring service health, troubleshooting…

labring/FastGPT · 84 tokens

android-resources

Organize Android strings, drawables, fonts, themes, localization, and concrete resource-backed Compose values such as MaterialTheme colors. Use for resource declarations and their direct UI lookup; defer design-system token architecture, network image loading, lint-rule configuration, and general Compose…

HoangNguyen0403/agent-skills-standard · 59 tokens