metadata.json
{
"description": "Skriv månedlige oppsummeringer av AI-nyheter for utviklere på norsk med fungerende kildelenker",
"domain": "general",
"tags": ["ai", "news", "research", "monthly-summary"],
"references": [
"references/OUTPUT-FORMAT.md"
],
"excluded": true
}
references/OUTPUT-FORMAT.md
# Output Format Reference
## Document structure
```markdown
# Nyheter og trender — [Måned] [År]
[One-sentence intro about what the month covered]
---
## 1. [Topic title]
[2-4 paragraphs explaining the news, what changed, and why it matters]
**Kilde:** [Title](https://exact-url) (source, date)
---
## 2. [Next topic]
...
---
## Relevans for Nav
[Table mapping trends to Nav-specific implications]
| Trend | Hva det betyr for Nav |
| ----- | --------------------- |
| ... | ... |
```
## Source citation rules
- Every section MUST end with a **Kilde:** or **Kilder:** block
- Links must be real, verified URLs — never fabricated
- Single source:
```markdown
**Kilde:** [Title](https://exact-url) (source, date)
```
- Multiple sources — blank line between header and list:
```markdown
**Kilder:**
- [Title](https://url) (source, date)
- [Title](https://url) (source, date)
```
## Markdown linting
- Blank line before and after every list
- Table separators with spaces: `| --- | --- |` not `|---|---|`
- No trailing whitespace
SKILL.md
---
name: ai-news-research
description: Skriv månedlige oppsummeringer av AI-nyheter for utviklere på norsk med fungerende kildelenker. Bruk for å skrive nyheter, oppsummere AI-trender, lage månedlig oppdatering, eller undersøke hva som er nytt i GitHub Copilot, coding agents, AGENTS.md, skills, memory, agentic workflows eller developer experience.
license: MIT
metadata:
domain: general
tags: ai news research monthly-summary
---
# AI News Research
Research AI coding agent news and write a monthly summary in Norwegian. Output: `docs/news/<month>.md`.
## Step 1: Search
Run web searches (adjust month/year):
```
GitHub Copilot news [month] [year]
AI coding agent trends [month] [year]
AI coding agent hardening readiness enterprise [year]
Reddit AI coding agents AGENTS.md skills context [year]
site:github.blog copilot
```
## Step 2: Fetch sources
For each hit, fetch the full page and extract facts, numbers, quotes, and the exact URL.
```
web_fetch url="https://github.blog/..." → extract announcements, dates, feature names
web_fetch url="https://news.ycombinator.com/..." → extract top comments, sentiment
```
| Source | What to look for |
| --- | --- |
| github.blog | Official announcements, feature launches, deep-dives |
| Hacker News | Community reactions, real-world experiences |
| Reddit | Practitioner sentiment, pain points, success stories |
| LinkedIn | Thought leaders, experience reports |
| Anthropic, OpenAI, Google | Competing platforms, trend reports |
## Step 3: Write the summary
Cover these topics when relevant news exists:
- **Platform updates**: Copilot, Agent HQ, competing platforms
- **Agent context**: AGENTS.md, skills, instructions, prompts
- **Memory**: Cross-agent memory, session persistence
- **Agentic workflows**: CI/CD, background agents, continuous AI
- **Security**: Sandboxing, safe outputs, access controls
- **Readiness**: Enterprise adoption, maturity models
- **SDK/extensibility**: Copilot SDK, MCP servers, custom agents
- **Community sentiment**: What developers actually experience
Write in Norwegian (bokmål), direct tone, short sentences. Use English tech terms where developers do (e.g. "public preview", "PR", "repo"). See [OUTPUT-FORMAT.md](./references/OUTPUT-FORMAT.md) for the exact document structure and source citation rules.
## Step 4: Nav relevance
End with a "Relevans for Nav" table. Nav context:
- GitHub Copilot as sanctioned AI coding tool, ~500 tech professionals
- Nais platform (Kubernetes/GCP), Kotlin/Ktor, Next.js
- Strong security/privacy/accessibility requirements
- Measures developer experience (SPACE framework, DORA metrics)
## Example output
See `docs/news/` in the repository root for published examples.