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/research-and-summarize

Distill complex topics into layered, actionable summaries. Start with the key insight, layer in detail, end with recommended next action.

shell
$ npx -y skills add DevelopersGlobal/ai-agent-skills --skill research-and-summarize --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/research-and-summarize
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

Distill complex topics into layered, actionable summaries. Start with the key insight, layer in detail, end with recommended next action.

SKILL.md

research-and-summarize.SKILL.md
name: research-and-summarize
description: Distill complex topics into layered, actionable summaries. Start with the key insight, layer in detail, end with recommended next action.
category: everyday
applies-to: [claude, gemini, cursor, copilot, any]
version: 1.0.0

Overview

Information overload is the default state. This skill transforms any research task into a structured summary: headline insight first, context second, detail third, action last. Designed for decision-makers who need clarity, not comprehensiveness.

When to Use

  • Summarizing technical documentation or papers
  • Researching a technology choice
  • Briefing a team on a topic
  • Distilling a long document for a specific decision

Process

Step 1: Define the Research Question

1. State the specific question being answered: *"Should we use Kafka or RabbitMQ for our event pipeline?"* 2. State who the answer is for and what decision it enables. 3. This scopes the research — don't gather information beyond what the decision needs.

**Verify:** Research question is specific enough to have a clear answer.

Step 2: Gather and Evaluate Sources

4. Identify 3–5 high-quality, authoritative sources. 5. For each source, note: recency, authority, potential bias. 6. Cross-reference key claims across sources. 7. Flag conflicting information — don't silently pick one side.

**Verify:** Key claims are supported by at least 2 independent sources.

Step 3: Write the Layered Summary

8. **Headline (1 sentence)**: The single most important insight. 9. **Key findings (3–5 bullets)**: Supporting evidence for the headline. 10. **Context and nuance (1–2 paragraphs)**: Caveats, tradeoffs, conditions under which the headline doesn't hold. 11. **What we don't know**: Gaps in the available information. 12. **Recommended action**: Given the findings, what should the reader do next?

**Deliver:** A structured summary with all 5 sections.

Step 4: Cite Sources

13. Every factual claim is linked to a source. 14. Include the date of each source (recency matters in fast-moving fields).

**Verify:** Every claim has a citation.

Common Rationalizations (and Rebuttals)

| Excuse | Rebuttal | |--------|----------| | "The topic is too complex to summarize" | The goal is to enable a decision, not to be comprehensive. Scope to the decision. | | "I'll just share the links" | Links are not summaries. Distillation is the value. |

Verification

  • [ ] Research question defined before research begins
  • [ ] Key claims cross-referenced across 2+ sources
  • [ ] Summary has: headline, findings, context, unknowns, action
  • [ ] Every factual claim has a citation with date

References

  • [think-before-coding skill](../think-before-coding/SKILL.md)
  • [idea-to-spec skill](../idea-to-spec/SKILL.md)
Read more
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AI agent skills for production grade applications

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Repo: DevelopersGlobal/ai-agent-skills