# Summarization

> Condense long context into concise, accurate summaries.

- Skill: `jonjonbinx1/summarization` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add jonjonbinx1/summarization`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jonjonbinx1/summarization/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: jonjonbinx1 (https://skillmd.com/u/jonjonbinx1)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/jonjonbinx1/summarization

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# Summarization

When context grows too long or you need to distill information, produce a concise summary that preserves essential meaning.

## When to Summarize

- File contents exceed what is needed for the current step.
- A research phase produced many results that need distillation.
- Conversation history is long and you need to recall key decisions.
- You need to report progress or results to the user.

## Process

1. **Identify the purpose.** Why is this summary needed? What question should it answer?

2. **Extract key facts.** Pull out:
   - Main conclusions or findings
   - Important data points, names, paths, or values
   - Decisions that were made
   - Open questions or unknowns

3. **Discard noise.** Remove:
   - Redundant information
   - Intermediate reasoning that is no longer needed
   - Verbose formatting or boilerplate

4. **Organize.** Structure the summary logically:
   - Lead with the most important finding
   - Group related facts together
   - Use bullet points for lists of items

5. **Verify accuracy.** Ensure the summary does not misrepresent the source. Do not infer facts that were not present.

## Output Format

```
Summary:
- <key point 1>
- <key point 2>
- ...

Open questions:
- <anything unresolved>
```

## Guidelines

- Aim for 20–30% of the original length unless told otherwise.
- Preserve exact values (paths, numbers, names) — do not paraphrase data.
- Summaries are lossy by nature. When in doubt, keep the fact.
- Attribute information to its source when summarizing multiple inputs.