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.md
source 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?