Here is the translated markdown content:

I created a ~75-second Chinese educational video about UFOs by combining Codex, HyperFrames, and Remotion. Based on a public repository on GitHub, this article explains how this repository organizes declassified UAP/UFO documents into a readable report. I divided the tasks as follows: HyperFrames was responsible for the actual video production, writing the visuals, text, transitions, and animation timeline in index.html, then using HyperFrames to check for overflow and sufficient contrast, and finally rendering to MP4. The final video you see was produced by HyperFrames. Remotion served as a structural reference, used to plan the duration of each shot, how transitions connect, and how the project should be organized if it were to be converted into a React/Remotion project later. I also included a Remotion reference skeleton in the current project, but Remotion was not used to render the final video this time. If you’re interested, you can check out this UFO collection repository: https://github.com/ckpxgfnksd-max/uap-release-analyzer…

ckpxgfnksd-max/uap-release-analyzer

Source: https://github.com/ckpxgfnksd-max/uap-release-analyzer

uap-release-analyzer

A Claude Code / Claude.ai skill that turns a folder of declassified UAP/UFO documents — war.gov “PURSUE” releases, FBI Vault tranches, NARA boxes, AARO publications — into a structured analytic report.

What it does

Run it against a release directory (e.g. ~/Documents/UFO/release_01/) and it produces:

• inventory.csv — one row per file: agency (inferred from filename prefix), document type, page count, size
• text/*.txt — extracted text via pdfplumber, with empty files flagged for the (often majority) of files that are scanned with no text layer
• analytics/
  • top_terms.csv, terms_by_agency.csv — token frequencies
  • entities.json — locations, agencies, phenomena vocabulary, year clusters, names appearing in 5+ files
  • per_file_digest.csv — top terms / locations / redactions / 2-sentence summary per file
  • cross_doc.json — redaction patterns, agency totals, scanned-vs-text split
• REPORT.md — 11-section human-readable analytic writeup

The four scripts are idempotent and incremental — re-running on the same folder skips work that’s already done.

Installation

# Inside Claude Code (per-user skills directory)
git clone https://github.com/ckpxgfnksd-max/uap-release-analyzer.git \
~/.claude/skills/uap-release-analyzer

Or package via skill-creator:

python -m scripts.package_skill /path/to/uap-release-analyzer # produces uap-release-analyzer.skill — install via Claude Code UI

Dependencies: pdfplumber, pypdf. Install via pip install pdfplumber pypdf.

Layout

uap-release-analyzer/
├── SKILL.md # frontmatter + workflow
├── scripts/
│   ├── inventory.py
│   ├── extract_text.py
│   ├── analyze.py
│   ├── build_report.py
│   └── run_all.py # convenience: run the four in order
├── references/
│   ├── agency_vocab.md # filename-prefix → agency rules
│   ├── foia_codes.md # FOIA exemptions and classification stamps
│   └── war_gov_quirks.md # how war.gov/UFO/ is structured + scraping notes
├── evals/evals.json # 4 test cases used to iterate the skill
├── ARTICLE.md # development notes (English)
├── ARTICLE_CN.md # 中文版开发笔记
└── LICENSE.txt

Usage

# One-shot: full pipeline
python scripts/run_all.py ~/Documents/UFO/release_01/

# Or step-by-step (inventory and extract are the slow parts; both are idempotent)
python scripts/inventory.py ~/Documents/UFO/release_01/
python scripts/extract_text.py ~/Documents/UFO/release_01/ # all files
python scripts/extract_text.py ~/Documents/UFO/release_01/ 0 25 # chunked
python scripts/analyze.py ~/Documents/UFO/release_01/
python scripts/build_report.py ~/Documents/UFO/release_01/

Example dataset

The May 2026 war.gov “PURSUE” release this skill was tuned against is mirrored at ckpxgfnksd-max/uap-release-01 (https://github.com/ckpxgfnksd-max/uap-release-01) (Git LFS, ~2.4 GB / 132 files / 4,157 PDF pages). Clone it as your release_01/ to reproduce the eval scoreboard:

git lfs install # one-time
git clone https://github.com/ckpxgfnksd-max/uap-release-01.git ~/Documents/UFO/release_01
python scripts/run_all.py ~/Documents/UFO/release_01

Or fetch only the buckets you care about (e.g., the text-bearing DOW mission reports):

GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/ckpxgfnksd-max/uap-release-01.git ~/Documents/UFO/release_01
cd ~/Documents/UFO/release_01
git lfs pull --include "dow-*"

Video is not mirrored — link to for any video material.

Eval scoreboard (iteration-1)

See ARTICLE.md for the build story and the bugs the eval surfaced.

Honest caveats

• Entity extraction is keyword-list + regex, not full NER. Year mentions ≠ incident dates.
• Scanned PDFs (no text layer) produce 0-char .txt files by design — the analyzer treats them as “OCR needed” rather than running OCR (multi-hour). Run Tesseract as a follow-up if you need that content searchable.
• The agency vocabulary is tuned to the May 2026 war.gov tranche. New tranches with new prefixes should be added to references/agency_vocab.md and scripts/inventory.py PREFIX_RULES.

License

MIT. See LICENSE.txt.