Tui Validate

TUI Validate

Overview

This skill validates Terminal User Interface (TUI) applications by capturing their output and using LLM-as-judge for semantic validation. It leverages freeze from Charmbracelet for high-fidelity terminal screenshots and provides structured validation criteria.

Philosophy: Rather than brittle string matching, this skill uses semantic understanding to validate that TUI output "looks right" - checking layout, content presence, and visual hierarchy without breaking on minor formatting changes.

When to Use

• Validating TUI rendering after changes
• Checking that UI components display correctly
• Visual regression testing for terminal applications
• Verifying TUI state after specific interactions
• Creating documentation screenshots with validation

Prerequisites

Required:

• freeze CLI tool installed (brew install charmbracelet/tap/freeze)
• tmux for interactive TUI capture (optional, for live applications)

Verification:

# Check freeze is installed
freeze --version

# Check tmux is installed (for interactive capture)
tmux -V

Parameters

• target (required): What to validate. One of:

  • file:<path> - ANSI output file to validate
  • command:<cmd> - Command to execute and capture
  • tmux:<session> - Live tmux session to capture
  • buffer:<text> - Raw text/ANSI to validate

• criteria (required): Validation criteria. Can be:

  • A predefined criteria name (see Built-in Criteria)
  • A custom criteria string describing what to check

• output_format (optional, default: "svg"): Screenshot format

  • svg - Vector format, best for documentation
  • png - Raster format, best for visual diff
  • text - Text-only extraction, fastest

• save_screenshot (optional, default: false): Whether to save the screenshot

  • If true, saves to {target_name}.{format} in current directory

• judge_mode (optional, default: "semantic"): Validation approach

  • semantic - LLM judges based on meaning and layout
  • strict - Also checks exact content presence
  • visual - Requires PNG, checks visual appearance

Built-in Criteria

ralph-header

Validates Ralph TUI header component:

• Iteration counter in [iter N] or [iter N/M] format
• Elapsed time in MM:SS format
• Hat indicator with emoji and name
• Mode indicator (▶ auto or ⏸ paused)
• Optional scroll mode indicator [SCROLL]
• Optional idle countdown idle: Ns

ralph-footer

Validates Ralph TUI footer component:

• Activity indicator (◉ active, ◯ idle, or ■ done)
• Last event topic display
• Search mode display when active

ralph-full

Validates complete Ralph TUI layout:

• Header section at top (3 lines)
• Terminal content area (variable height)
• Footer section at bottom (3 lines)
• Proper visual hierarchy and borders

tui-basic

Generic TUI validation:

• Has visible content (not blank)
• No rendering artifacts or broken characters
• Proper terminal dimensions

Execution Flow

1. Capture Phase

Capture TUI output based on target type:

For file targets:

freeze {file_path} -o /tmp/tui-capture.{format}

For command targets:

freeze --execute "{command}" -o /tmp/tui-capture.{format}

For tmux targets:

tmux capture-pane -pet {session} | freeze -o /tmp/tui-capture.{format}

For buffer targets:

echo "{buffer}" | freeze -o /tmp/tui-capture.{format}

Constraints:

• You MUST verify freeze is installed before attempting capture
• You MUST handle capture failures gracefully and report the error
• You MUST use appropriate freeze flags for the output format
• You SHOULD use --theme base16 for consistent rendering
• You SHOULD set reasonable dimensions with --width and --height

2. Extraction Phase

Extract content for LLM analysis:

For text/semantic validation:

• If format is text, use the captured text directly
• If format is svg or png, also capture text version for content analysis

For visual validation:

• Requires PNG format
• Will analyze the image directly using vision capabilities

Constraints:

• You MUST extract both visual and text representations when judge_mode is visual
• You MUST preserve ANSI escape sequences for color validation when relevant

3. Validation Phase

Apply LLM-as-judge with the appropriate criteria:

Semantic Validation Prompt Template:

Analyze this terminal UI output and determine if it meets the following criteria:

CRITERIA:
{criteria_description}

TERMINAL OUTPUT:
{captured_text}

Evaluate each criterion and provide:
1. PASS or FAIL for each requirement
2. Brief explanation for any failures
3. Overall verdict: PASS or FAIL

Be lenient on exact formatting but strict on:
- Required content presence
- Logical layout and hierarchy
- No rendering errors or artifacts

Visual Validation Prompt Template (with image):

Examine this terminal screenshot and validate:

CRITERIA:
{criteria_description}

Check for:
1. Visual hierarchy and layout
2. Color coding correctness
3. No rendering artifacts or broken characters
4. Proper alignment and spacing

Verdict: PASS or FAIL with explanation

Constraints:

• You MUST return a clear PASS or FAIL verdict
• You MUST provide specific feedback on failures
• You MUST be lenient on whitespace/formatting differences
• You MUST be strict on content presence and semantic correctness
• You SHOULD note any warnings even on PASS results