tcr-apply

Generates three additive Transparency, Control, and Recovery prompts tailored to an existing UI pattern.

Updated Jun 3, 2026
One-click install
npx skills add https://github.com/MathematicGuy/team-006-vin20k --skill tcr-apply-mathematicguy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tcr-apply
Source: https://github.com/MathematicGuy/team-006-vin20k/tree/main/ai20k-ux-workshop/.agents/skills/tcr-apply
Command: npx skills add https://github.com/MathematicGuy/team-006-vin20k --skill tcr-apply-mathematicguy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Students with a working AI app demo often struggle to improve UX systematically. This Skill reads the existing codebase, detects which of seven UI patterns the app matches, and produces three copy-paste prompts that layer Transparency, Control, and Recovery features onto the app without rewriting it. ## Core Features & Use Cases - UI Pattern Detection: Scans the repo for signals (chat components, upload handlers, queues, streaming) and classifies the app into one of seven UI patterns. - Three Tailored Prompts: Emits a Prompt T (Transparency), Prompt C (Control), and Prompt R (Recovery), each under 80 words, additive-only, and localized to the app's existing UI language. - Reasoning Included: Every prompt ships with a "Why" explanation so students build intuition for the T-C-R framework. - Use Case: After demoing a working RAG chatbot, a student asks how to improve UX. The skill detects the chat-plus-panel pattern and returns prompts to add a sources panel with confidence colors, a stop button with AbortController, and a retry-on-error flow. ## Quick Start Run /tcr-apply from the repository root of a working AI app and ask it to retrofit the T-C-R pattern onto the existing UI.

Frequently Asked Questions about tcr-apply

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add Transparency, Control, and Recovery features to an existing AI chat app?▼

Run the skill from the repo root of your working app. It detects the UI pattern from your code and returns three sequential prompts — one each for Transparency, Control, and Recovery — that you paste into Claude Code one at a time, reviewing and committing after each.

What UI patterns does the T-C-R retrofit support?▼

Seven patterns are supported: chat with context panel, upload-to-dashboard, query-to-structured-result, wizard with inline audit, draft-approve-send, queue with approval, and real-time streaming. Detection uses code signals like st.chat_message, file uploaders, SQL runners, and EventSource usage.

Does the skill rewrite my existing app or change its file structure?▼

No. Every generated prompt is explicitly additive — it adds new components and features without refactoring, restructuring, or moving existing files. Anti-patterns like bundling all three prompts into one or prescribing specific component libraries are forbidden.

What happens if the skill cannot detect my app's UI pattern?▼

If code signals are weak or ambiguous, the skill lists the seven pattern names and asks which one closest matches your app instead of guessing silently. A wrong pattern guess would produce wrong prompts, so it confirms first.

Can the generated prompts match a Vietnamese-language UI?▼

Yes. The skill reads your app's existing UI strings (button labels, placeholders, JSX copy) and mirrors that language in the generated prompts. If a GUIDELINE.md file exists from a prior ui-pattern run, it uses that to pick domain-specific copy and trust-signal types.

Why should I paste the three prompts one at a time instead of together?▼

The T-C-R features are designed to compound sequentially. Pasting one prompt, reviewing the diff, testing in the browser, and committing before the next keeps each change reviewable and preserves the pedagogical rhythm of the workshop.