Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Chain-of-Density (CoD) is an iterative summarization method from a 2023 research paper. It compresses text through 5 passes, each identifying missing entities from the source and injecting them into the summary while holding word count constant. The result is a fixed-length summary that grows progressively more specific with each iteration.
Unlike one-shot summarization, CoD forces entity accumulation across iterations, so the final summary contains more named specifics at the same length rather than generic paraphrase.
When to use it
- Condensing verbose API documentation into a fixed-length reference
- Compressing long requirements documents for executive review
- Summarizing research papers while preserving key terminology
- Reducing overlong agent skill files to meet length limits
- Creating dense briefings from detailed incident reports
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Summarize this 600-word architecture document in 80 words
- 1Pass source text to cod-iteration agent as iteration 1 to produce a sparse base summary
- 2Parse the Missing_Entities line and Denser_Summary from the response
- 3Pass both the previous summary and original source to cod-iteration for iterations 2 through 5
- 4Track accumulated entities across all iterations
- 5Return the final dense summary and optionally the full iteration history
An 80-word summary containing 9+ specific entities from the source, with optional YAML history showing entity accumulation per pass