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Thesis Defense Pptx

Community
zouchenzhen
thesis-defense-pptx

Create, polish, and quality-check editable undergraduate or graduate thesis defense PowerPoint decks from a local thesis PDF/LaTeX project and an existing PPTX template. Use when the user asks for a formal defense PPT, thesis presentation, academic答辩PPT, template-matched PPTX, or local PowerPoint deck generation with visual inspection.

Overview

Publisherzouchenzhen
Repositorythesis-defense-pptx-skill
Skill namethesis-defense-pptx
Stars
275
Forks
19
Bundled files
11
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zouchenzhen on GitHub. Read the source before you install it.

Installation

Install the Thesis Defense Pptx AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zouchenzhen/thesis-defense-pptx-skill/tree/main/skills/thesis-defense-pptx
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zouchenzhen/thesis-defense-pptx-skill.git /tmp/thesis-defense-pptx-skill
mkdir -p .claude/skills
cp -r /tmp/thesis-defense-pptx-skill/skills/thesis-defense-pptx .claude/skills/thesis-defense-pptx
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Thesis Defense Pptx in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Thesis Defense Pptx on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Thesis Defense Pptx is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Thesis Defense PPTX

Use this skill for local, editable .pptx thesis defense decks that must follow a supplied university/lab/company PowerPoint template.

Operating Principles

  • Platform: Windows + Microsoft PowerPoint for COM-driven cloning, export, and overflow inspection. On macOS/Linux, use the python-pptx-only parts and skip COM-based quality gates.
  • Treat the visual template as the source of truth. Preserve its cover, colors, fonts, navigation, card styles, logos, and slide proportions unless the user explicitly asks to redesign.
  • Read the thesis source first: PDF, LaTeX, figures, old PPT, experiment scripts, tables, and captions. Do not generate from topic/title alone when source files exist.
  • Build a source-asset inventory before placing images: extract \includegraphics entries and captions from the final TeX/PDF, then use only thesis-cited figures or images the user explicitly approves. Do not carry over pictures from a template, old progress deck, or draft figure folder merely because they look relevant.
  • Prefer copying native template slides and replacing content over rebuilding from blank slides.
  • Keep slides concise and presentation-oriented. Convert thesis prose into defense talking points.
  • Preserve the template's font sizes and hierarchy by default. For projection readability, first shorten text, split dense slides, or use the template's larger existing layouts; only change font sizes locally when the template itself provides no readable fit.
  • Always generate an editable .pptx, not only an outline, image deck, PDF, or HTML.
  • Always run a visual quality gate before final response: export slide images, inspect a contact sheet plus key full-size slide screenshots, check text overflow, check stale template words/images, and verify the PPTX opens.

Recommended Workflow

  1. Identify inputs:

    • thesis project path or full thesis document
    • visual template PPTX
    • optional old defense/report PPTX
    • output directory and desired filename
  2. Extract thesis context:

    • Use scripts/extract_thesis_context.py to summarize PDF/TeX text and list candidate figures.
    • Read source files directly when details matter: abstract, introduction, method, experiments, results, conclusion.
    • Create an explicit list of final-thesis figures from \includegraphics and captions. Treat this as the allow-list for PPT images unless the user requests new visuals.
    • Collect defense-critical facts: problem, motivation, modeling, algorithms, experimental setup, baselines, metrics, key results, limitations, future work.
  3. Analyze the template:

    • Export template slides to PNG if PowerPoint is available.
    • Inspect cover, TOC, navigation, section, body/card, chart/image, summary, and closing slide styles.
    • Note fonts, font sizes, red/brand color, card dimensions, line widths, and spacing.
  4. Build a native template skeleton:

    • Use PowerPoint COM (scripts/clone_template_deck.ps1) when PowerPoint is installed.
    • Copy or duplicate original template slides in the needed order.
    • Use python-pptx only to replace content and add images/shapes after the skeleton is valid.
  5. Fill content:

    • Use 12-16 slides for undergraduate defense unless user specifies otherwise.
    • Typical order: cover, TOC, background, problem definition, work summary, system/method, modeling, implementation, experiment setup, training/results, comparison, robustness/multi-seed, innovation/limitations, summary/outlook, thanks.
    • Use final-thesis figures first and verify each inserted picture against the source-asset inventory. If a picture is from a template or old deck and is not thesis-cited, replace it or remove it.
    • Keep dense tables limited to headline metrics; move detailed prose into verbal notes or omit. Prefer one message per slide, large existing template placeholders, metric cards, and short bullets over shrinking text or adding small multi-column tables.
    • Match the template's typography before changing sizes: preserve title/body/table/navigation sizing where possible, and use content reduction or slide splitting before manual font scaling.
  6. Quality gate:

    • Export final PPTX to PNG with scripts/export_pptx_png.ps1.
    • Create a contact sheet with scripts/make_contact_sheet.py.
    • Run scripts/inspect_pptx_overflow.ps1.
    • Run scripts/scan_pptx_text.py for slide count and stale template terms.
    • Inspect the contact sheet manually, then open any risky slide full-size. COM overflow is not sufficient: also check visible clipping, text crossing card borders, small text caused by overfilling, stale template images, image aspect ratios, and text/card overlap.
    • Check stale template text, placeholders, wrong names/dates, wrong navigation labels, red active-nav white text, and non-thesis images accidentally inherited from the template or old progress deck.
    • Fix and repeat until the exported deck is clean.
  7. Final response:

    • Give the full output path, total slide count, main changes, validation performed, and any unresolved manual confirmations.

Script Usage

Extract thesis context:

powershell
python scripts/extract_thesis_context.py --input "D:\path\to\thesis" --output "D:\path\to\thesis_context.md"

Clone template slides into a native skeleton:

powershell
powershell -NoProfile -ExecutionPolicy Bypass -File scripts/clone_template_deck.ps1 `
  -Template "D:\path\template.pptx" `
  -Output "D:\path\output.pptx" `
  -SlideSequence "1,2,3,4,4,6,7,8,9,10,11,12,13,14,15"

In this example slide 4 is deliberately reused as a sub-section page and slide 5 is skipped.

Export final deck:

powershell
powershell -NoProfile -ExecutionPolicy Bypass -File scripts/export_pptx_png.ps1 `
  -Pptx "D:\path\output.pptx" `
  -OutDir "D:\path\visual_check" `
  -Width 1600 -Height 900

Inspect possible overflow:

powershell
powershell -NoProfile -ExecutionPolicy Bypass -File scripts/inspect_pptx_overflow.ps1 `
  -Pptx "D:\path\output.pptx" `
  -Tolerance 40 `
  -OutputJson "D:\path\overflow.json"

Make a contact sheet:

powershell
python scripts/make_contact_sheet.py --input "D:\path\visual_check" --output "D:\path\contact_sheet.png"

Scan deck text and forbidden terms:

powershell
python scripts/scan_pptx_text.py `
  --pptx "D:\path\output.pptx" `
  --bad "中期检查,项目简介,系统框图,算法设计,成果展示,总结分析,TODO,占位"

For quality criteria, read references/pptx_quality_gate.md.

Iteration Tips

The fastest way to fail a content fill is guessing strings instead of reading them. Use this loop:

  1. Dump first. Run scripts/dump_pptx_content.py --pptx <skeleton> --output dump.md to list every shape's exact text, plus all table cells and picture names. Open dump.md and copy the strings you intend to replace.
  2. Prefer partial match for body text. Use replace_partial_text(slide, {"keyword": "new full text"}) instead of replace_exact_text whenever the body sentence might differ from the template by a stray space, half/full-width quote, or —— vs —. Pass min_len=20 to avoid short-key collisions with navigation tags.
  3. Keep replace_exact_text for short tags. Navigation labels and section titles ("项目简介", "工作总结") are stable; exact match is safer because it cannot accidentally rewrite a body paragraph that happens to contain the same word.
  4. Use the table/picture helpers. write_table(table, rows) preserves cell font/color/size, and replace_picture(slide, old_pic, new_path) swaps an image while keeping position and size — both avoid the boilerplate of removing and re-creating shapes.
  5. Re-run overflow + scan after every fill pass. Overflow caused by longer content is the single most common bug; fix by shortening copy first, then by manual \n line breaks, and only resize the textbox if the template visual really allows it.
  6. Encoding. All Python scripts shipped here force stdout to UTF-8, and the PowerShell scripts force the console output codepage to UTF-8, so cp936/gbk consoles do not corrupt JSON output containing CJK paths or Unicode symbols (−, Δ, ✓).

Script Usage

Dump every slide's shapes/text/tables/pictures (run this BEFORE constructing replacement dicts):

powershell
python scripts/dump_pptx_content.py --pptx "D:\path\skeleton.pptx" --output "D:\path\dump.md"

Add --slide 4,8,9 to limit to specific slides while iterating.

Implementation Notes

  • Requires Python 3.10+ and the packages in requirements.txt.
  • On Windows with Microsoft PowerPoint installed, PowerPoint COM is the most reliable way to duplicate template slides and inspect real rendering.
  • python-pptx is good for editable text, shapes, images, tables, and simple charts, but it does not perfectly model every PowerPoint layout/rendering behavior.
  • scripts/pptx_template_tools.py uses THESIS_PPTX_BRAND_RED when set (#830604, 830604, or 131,6,4) so new school templates do not require source edits for the primary red.
  • When a PowerPoint add-in blocks COM automation, disable only the broken add-in autoload if necessary and report that action.
  • Use backups before overwriting a deck.
  • Never revert unrelated user files while iterating.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Thesis Defense Pptx AI skill do?

Create, polish, and quality-check editable undergraduate or graduate thesis defense PowerPoint decks from a local thesis PDF/LaTeX project and an existing PPTX template. Use when the user asks for a formal defense PPT, thesis presentation, academic答辩PPT, template-matched PPTX, or local PowerPoint deck generation with visual inspection.

Why use Thesis Defense Pptx on TypingMind?

Because you install it once and use it with any model. Thesis Defense Pptx is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Thesis Defense Pptx in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zouchenzhen/thesis-defense-pptx-skill/tree/main/skills/thesis-defense-pptx. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Thesis Defense Pptx?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Thesis Defense Pptx?

As many as you like. As long as a model supports skills, you can use Thesis Defense Pptx with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Thesis Defense Pptx AI skill free?

Yes. It is published on GitHub by zouchenzhen under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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