A professional-grade framework for triaging, grading, and reporting on declassified UAP, UFO, and FOIA document releases from multiple official sources.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ufo
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ufo using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is UFO Research Workbench?
The UFO Research Workbench is a specialized toolkit designed for Openclaw Skills that transforms raw declassified document folders into structured analytic artifacts. It moves beyond simple text extraction by implementing a rigorous five-layer workflow that includes multi-source triage, claim taxonomy, and evidence-provenance scoring. This skill is built for researchers who require a high level of technical rigor, treating every document as a claim-bearing artifact rather than absolute ground truth.
By leveraging the power of Openclaw Skills, this workbench enforces mandatory uncertainty labeling and skepticism guardrails. It allows analysts to distinguish between official document claims, inferred patterns, and verified facts. Whether you are analyzing a single FBI Vault tranche or comparing multiple congressional hearing releases, this skill provides the structured framework necessary for high-integrity UAP investigations.
UFO Research Workbench Use Cases
- Analyzing and triaging large folders of declassified UAP documents from war.gov or AARO.
- Comparing different versions of FOIA releases to identify new redactions or text changes.
- Building evidence matrices and chronologies for congressional hearing transcripts.
- Mapping entity relationships and timelines across multiple government agency memos.
- Generating structured executive briefs and uncertainty registers for UAP research projects.
How UFO Research Workbench Works
- Source Triage: The skill classifies the release source (e.g., FBI, NARA, AARO) to establish a baseline reliability profile.
- Inventory & Extraction: Python scripts generate a file inventory and extract text layers from PDFs using pdfplumber.
- Claim Taxonomy: Extracted text is categorized into specific types such as sightings, sensor data, or whistleblower testimony.
- Evidence Grading: Each claim is scored on a 5.0 scale based on source reliability, corroboration, and information specificity.
- Artifact Generation: The agent produces a comprehensive bundle including an Evidence Matrix, Redaction Heatmap, and Executive Brief.
UFO Research Workbench Setup
To use this skill within Openclaw Skills, ensure you have the necessary Python dependencies installed for text processing:
python3 -m pip install pdfplumber pypdf
Once dependencies are met, you can point the agent to a local directory containing your UAP document releases to begin the triage and analysis process.
UFO Research Workbench Data Schema & Taxonomy
The skill organizes its findings into a standardized artifact bundle to ensure consistency across different research projects:
| Artifact | File Name | Description |
|---|---|---|
| Release Inventory | inventory.csv |
Metadata for every file including source provenance tags. |
| Evidence Matrix | evidence-matrix.md |
Claims graded by reliability and sorted by score. |
| Chronology | chronology.md |
A temporal map of events with explicit uncertainty flags. |
| Redaction Heatmap | redaction-heatmap.md |
Analysis of FOIA exemptions and withheld data patterns. |
| Uncertainty Register | uncertainty-register.md |
A log of all assumptions, inferences, and data gaps. |
UFO Research Workbench Advanced Features
- Cross-Release Diffing: Automatically detect changes in file size, text content, and redaction patterns between different release dates.
- Provenance Scoring Rubric: A multi-axis grading system that weights source reliability and corroboration for objective analysis.
- Mandatory Uncertainty Labeling: Built-in guardrails that tag every finding as
[DOC CLAIM],[INFERRED], or[VERIFIED]to prevent hallucination. - Entity Mapping: Automated identification of organizations, programs, and individuals mentioned across fragmented document sets.
- Idempotent Extraction: Scripts are designed to be chunkable and repeatable, making them suitable for massive datasets without data loss.
SKILL.md
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