create-presentation

name	create-presentation
description	Generate a PPTX presentation explaining code changes on the current branch, with matplotlib diagrams and dark theme slides.
argument-hint	[base-branch]
user-invocable	true

Generate a PPTX presentation explaining the changes on the current branch.

Arguments

If "$ARGUMENTS" is non-empty, use it as the target branch to compare against. Otherwise, default to origin/develop.

Task

You are creating a technical presentation for a team of developers. The output is a .pptx file in the project root that the user can open in Google Slides.

Step 1 — Investigate the branch

1. Run git log --oneline <base>..HEAD to list all commits on this branch.
2. Run git diff --name-only <base>..HEAD to find changed source files.
3. Separate generated files (e.g. sql/parser/YouTrackDBSql*.java) from hand-written code.
4. Read every non-generated changed source file to understand the full picture.
5. Read commit messages for motivation and design rationale.

Step 2 — Plan the slides

Create a slide outline (15–25 slides) covering:

• Title slide with branch name and issue ID (extracted from branch name).
• Problem statement — what motivated this change.
• Solution overview — high-level summary with a phase/flow diagram.
• Architecture slides — new files, data structures, on-disk formats.
• Algorithm slides — step-by-step flowcharts for key algorithms.
• Code path slides — how existing code is modified and where new code hooks in.
• Configuration — new parameters, defaults, tuning guidance.
• Safety properties — crash safety, concurrency, error handling.
• Design decisions — key trade-offs and rationale.
• Scope/limitations — what is NOT covered.
• Q&A slide.

Step 3 — Set up Python environment

python3 -m venv .tmp/pptx-venv
.tmp/pptx-venv/bin/pip install python-pptx matplotlib

If the venv already exists, skip creation and just verify imports work.

Step 4 — Generate diagrams with matplotlib

For every diagram (flowcharts, architecture, data flow, record layouts, before/after comparisons), generate a matplotlib figure rendered to a PNG BytesIO stream.

Follow these conventions:

Color theme (dark, matches slide background)

MPL_BG      = '#121224'   # figure/axes background
MPL_FG      = '#e0e0e0'   # default text
MPL_BLUE    = '#64B5F6'   # titles, primary boxes
MPL_LBLUE   = '#81D4FA'   # secondary highlights
MPL_GREEN   = '#A5D6A7'   # success/safe elements
MPL_ORANGE  = '#FFB74D'   # accent/new/warning
MPL_RED     = '#EF5350'   # delete/danger
MPL_BOX_BG  = '#1a2a44'   # box fill
MPL_BOX_BORDER = '#3a5a8a'  # box stroke

Diagram building blocks

Use matplotlib.patches.FancyBboxPatch for boxes and ax.annotate with arrowprops for arrows. Helper pattern:

def make_box(ax, x, y, w, h, text, facecolor, edgecolor, text_color,
             fontsize=11, weight='normal'):
    box = FancyBboxPatch((x, y), w, h, boxstyle="round,pad=0.15",
                         facecolor=facecolor, edgecolor=edgecolor, linewidth=1.5)
    ax.add_patch(box)
    ax.text(x + w/2, y + h/2, text, ha='center', va='center',
            fontsize=fontsize, color=text_color, weight=weight, family='monospace', wrap=True)

def make_arrow(ax, x1, y1, x2, y2, color='#81D4FA', style='->', lw=2):
    ax.annotate('', xy=(x2, y2), xytext=(x1, y1),
                arrowprops=dict(arrowstyle=style, color=color, lw=lw))

Figure setup

• Always use matplotlib.use('Agg') before importing pyplot.
• Use fig.savefig(buf, format='png', dpi=200, bbox_inches='tight', facecolor=fig.get_facecolor()).
• Turn off axes: ax.axis('off').
• Use figsize appropriate for widescreen (e.g. (12, 5) for wide diagrams, (10, 7) for tall ones).

What NOT to do for diagrams

• Do NOT use Pillow ImageDraw.text() to render ASCII art — the default bitmap font has broken glyph coverage for box-drawing characters (U+250x) and the output is unreadable in presentations.
• Do NOT use mermaid-py or mermaid-cli — they require network access or a headless browser, neither of which is reliably available.
• Do NOT use the graphviz Python package — it requires the dot binary which may not be installed.
• matplotlib is the ONLY reliable local renderer. Use it for ALL diagrams.

Step 5 — Build the PPTX

Use python-pptx to assemble slides. Follow these conventions:

Slide dimensions

prs.slide_width = Inches(13.333)   # widescreen 16:9
prs.slide_height = Inches(7.5)

PPTX color theme

BG_COLOR        = RGBColor(0x1B, 0x1B, 0x2F)  # slide background
TITLE_COLOR     = RGBColor(0x64, 0xB5, 0xF6)  # slide titles
HEADING_COLOR   = RGBColor(0x81, 0xD4, 0xFA)  # subtitles
TEXT_COLOR      = RGBColor(0xE0, 0xE0, 0xE0)  # body text
ACCENT_COLOR    = RGBColor(0xFF, 0xB7, 0x4D)  # bold highlights
CODE_BG         = RGBColor(0x12, 0x12, 0x24)  # code block fill
TABLE_HEADER_BG = RGBColor(0x1A, 0x3A, 0x5C)  # table header row
TABLE_ROW_BG    = RGBColor(0x15, 0x15, 0x2A)  # odd table rows
TABLE_ALT_BG    = RGBColor(0x1D, 0x1D, 0x35)  # even table rows
BORDER_COLOR    = RGBColor(0x3A, 0x3A, 0x5C)  # code block border

Slide structure

• Use prs.slide_layouts[6] (blank layout) for all slides.
• Set background: slide.background.fill.solid(); slide.background.fill.fore_color.rgb = BG_COLOR.
• Title: 32pt, bold, TITLE_COLOR, positioned at (0.5", 0.3").
• Body text: 17–18pt, TEXT_COLOR. Use **bold** parsing to apply ACCENT_COLOR.
• Code blocks: ROUNDED_RECTANGLE shape with CODE_BG fill, Consolas 13pt, green text.
• Tables: styled with alternating row colors, header row in TABLE_HEADER_BG.
• Diagrams: inserted as PNG images via slide.shapes.add_picture(stream, left, top, width).

Code organization

Write the entire generator as a single Python script saved to .tmp/gen-presentation.py. Structure it as:

1. Imports and theme constants.
2. matplotlib diagram generator functions (one per diagram).
3. PPTX helper functions (set_slide_bg, add_title, add_bullet_text, add_code_block, add_table, add_image).
4. Slide-by-slide assembly.
5. prs.save(output_path) at the end.

Run with: .tmp/pptx-venv/bin/python .tmp/gen-presentation.py

Step 6 — Output

Save the PPTX to the project root as <branch-name>-presentation.pptx. Tell the user the file path and total slide count. Also leave the Python script at .tmp/gen-presentation.py so the user can tweak and regenerate.

Quality checklist

• Every diagram is a matplotlib-rendered PNG — no ASCII art in the final PPTX.
• Diagrams use the dark color theme and render at 200 DPI.
• All text is legible (minimum 10pt in diagrams, 13pt in code blocks, 17pt in body).
• Slide count is between 15 and 25.
• The presentation tells a coherent story: problem → solution → details → safety → decisions.
• No broken images or placeholder text.