ai-output-validation
Validates, parses, and sanitizes AI-generated outputs before they reach end users or downstream systems. Structured output enforcement, schema validation, and…
Distill complex topics into layered, actionable summaries. Start with the key insight, layer in detail, end with recommended next action.
$ npx -y skills add DevelopersGlobal/ai-agent-skills --skill research-and-summarize --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/research-and-summarizeContext 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.
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
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.
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.
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.
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.
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.
| 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. |
AI agent skills for production grade applications
Validates, parses, and sanitizes AI-generated outputs before they reach end users or downstream systems. Structured output enforcement, schema validation, and…
Design stable, versioned, self-documenting APIs. Easy to use correctly, hard to use incorrectly. Apply Hyrum's Law from day one.
Automated quality gates from commit to production. Every merge to main is potentially shippable. No manual steps in the deployment path.
Get layered, context-aware explanations of unfamiliar code. Understand what it does, why it was written that way, and how to work with it safely.
Structured code review focusing on correctness, security, and maintainability. Correctness before style. Every reviewer comment must be actionable.
Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.