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.
curl -O https://raw.githubusercontent.com/guillermoscript/lms-front/master/.agents/skills/adapt/SKILL.mdgit clone --depth 1 https://github.com/guillermoscript/lms-frontWrote 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/guillermoscript/lms-front/adapt)<a href="https://agentmods.dev/skills/guillermoscript/lms-front/adapt"><img src="https://agentmods.dev/badge/skills/guillermoscript/lms-front/adapt/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.
<a href="https://agentmods.dev/skills/guillermoscript/lms-front/adapt"><img src="https://agentmods.dev/badge/skills/guillermoscript/lms-front/adapt.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00026 | $0.01472 |
| Opus 5.5 | $0.00010 | $0.00589 |
| Sonnet 5.5 | $0.00005 | $0.00294 |
| Haiku 4.5 | $0.00003 | $0.00147 |
Grade A, and why
adapt 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.
This is a copy
88% identical to adapt — 20 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adapt existing designs to work effectively across different contexts - different screen sizes, devices, platforms, or use cases.
Assess Adaptation Challenge
Understand what needs adaptation and why:
-
Identify the source context:
- What was it designed for originally? (Desktop web? Mobile app?)
- What assumptions were made? (Large screen? Mouse input? Fast connection?)
- What works well in current context?
-
Understand target context:
- Device: Mobile, tablet, desktop, TV, watch, print?
- Input method: Touch, mouse, keyboard, voice, gamepad?
- Screen constraints: Size, resolution, orientation?
- Connection: Fast wifi, slow 3G, offline?
- Usage context: On-the-go vs desk, quick glance vs focused reading?
- User expectations: What do users expect on this platform?
-
Identify adaptation challenges:
- What won't fit? (Content, navigation, features)
- What won't work? (Hover states on touch, tiny touch targets)
- What's inappropriate? (Desktop patterns on mobile, mobile patterns on desktop)
CRITICAL: Adaptation is not just scaling - it's rethinking the experience for the new context.
Plan Adaptation Strategy
Create context-appropriate strategy:
Mobile Adaptation (Desktop → Mobile)
Layout Strategy:
- Single column instead of multi-column
- Vertical stacking instead of side-by-side
- Full-width components instead of fixed widths
- Bottom navigation instead of top/side navigation
Interaction Strategy:
- Touch targets 44x44px minimum (not hover-dependent)
- Swipe gestures where appropriate (lists, carousels)
- Bottom sheets instead of dropdowns
- Thumbs-first design (controls within thumb reach)
- Larger tap areas with more spacing
Content Strategy:
- Progressive disclosure (don't show everything at once)
- Prioritize primary content (secondary content in tabs/accordions)
- Shorter text (more concise)
- Larger text (16px minimum)
Navigation Strategy:
- Hamburger menu or bottom navigation
- Reduce navigation complexity
- Sticky headers for context
- Back button in navigation flow
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.
- 1mo ago First seen · 198 lines · 26 tokens per session scan A f4f88ca97b5b
adapt is a skill published in the GitHub repository guillermoscript/lms-front (40 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 1,472 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to adapt, differing in 20 lines, and is treated as a copy.
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