Desktop document-summary
Document summarization and interpretation — long document distillation, multi-level summaries (one-line/paragraph/detailed), key information extraction.
install
source · Clone the upstream repo
git clone https://github.com/openyak/openyak
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openyak/openyak "$T" && mkdir -p ~/.claude/skills && cp -r "$T/backend/app/data/skills/document-summary" ~/.claude/skills/openyak-desktop-document-summary && rm -rf "$T"
manifest:
backend/app/data/skills/document-summary/SKILL.mdsource content
Document Summarization and Interpretation
When the user provides a document (PDF, article, report, contract, etc.) and asks for a summary or interpretation, follow this workflow:
1. Read and understand
For local files, use
read to access them directly. For large or complex files (e.g., parsing Excel, extracting PDF tables), use write + bash to write a Python script for processing.
First pass: Skim
- Title, table of contents, section headings
- Charts and tables
- Abstract/conclusion sections (if present)
- Build a mental model of the document's structure
Second pass: Deep read
- Core arguments and key data
- Topic sentence of each section
- Author's position and recommendations
- Technical terms and key concepts
2. Summary levels
Provide different depths based on what the user needs:
One-line summary
- Capture the document's core message in a single sentence
- Format: [document topic] + [core finding/conclusion]
Paragraph summary (100-300 words)
- 3-5 sentences covering:
- Document topic and purpose
- Core findings (2-3)
- Main conclusion or recommendation
Detailed summary (500-1000 words)
- Organized following the original document's structure
- Key points from each major section
- Preserve critical data and citations
- Include the author's analysis and recommendations
Structured summary
- Use headings, bullet points, and tables to organize information
- Best for documents that need to be quickly searchable
3. Key information extraction
Focus on different elements depending on document type:
Research reports / White papers
- Core findings and data
- Market size / growth rates
- Key trends
- Recommendations and forecasts
News articles
- 5W1H (Who/What/When/Where/Why/How)
- Core event and impact
- Reactions and commentary from stakeholders
Business contracts / Legal documents
- Parties involved
- Core terms and obligations
- Amounts and timelines
- Special clauses and risk points
Technical documentation
- Core features/capabilities
- Prerequisites and limitations
- Key parameters and metrics
- Important caveats
Academic papers
- Research question and hypotheses
- Methodology
- Core findings
- Limitations and future directions
4. Interpretation and analysis
Beyond summarization, the user may want:
- Simplification: Explain technical content in plain language
- Critical analysis: Identify logical gaps, data issues, or bias
- Comparative analysis: Compare with other related documents/viewpoints
- Practical advice: Suggest actions based on the document's content
- Q&A: Answer specific questions about the document
5. Output format
- Use Markdown formatting
- Bold key data and conclusions
- Use > blockquote format for direct citations from the original
- Use tables for large amounts of data
- Start the summary with document metadata:
- Document title
- Author / source
- Date
- Page count / word count
6. Quality checklist
- Does the summary cover the document's core information?
- Does it accurately reflect the original's stance and viewpoint?
- Are personal judgments clearly labeled as such?
- Are key data citations accurate?
- Does the summary length match the user's request?
- Could someone understand the document's gist from the summary alone?