Skill: a1437707640-ui/high-quality-info-sources (version 1.0.0)

--- name: high-quality-info-sources description: Build, curate, score, and maintain high-quality information source lists for AI, technology, business, or any topic. Use when the user asks to create a skill for trusted sources, make a watchlist of people/sites/accounts to follow, filter noisy sources into a smaller high-signal set, turn a link dump into a reusable monitoring system, or design a repeatable workflow for tracking official accounts, researchers, critics, and market signals. --- # High-Quality Info Sources Build a small, high-signal information radar instead of a giant attention landfill. ## Core workflow 1. Clarify the monitoring goal. 2. Group sources by role, not by popularity. 3. Prefer primary sources over commentary. 4. Keep the default list small. 5. Add a review rule so the list stays useful. ## Clarify the monitoring goal Start by identifying what the user actually wants to track: - breaking product/model releases - research progress - developer ecosystem changes - market/industry moves - critical or skeptical takes - company-specific monitoring If the user does not specify, assume they want a balanced monitoring set with: - official release channels - technical interpreters - industry operators - critics / risk voices ## Group by source role Do not return a flat pile of links unless explicitly requested. Organize sources into roles such as: - **Official / primary** — company accounts, labs, docs, release blogs - **Builders / operators** — founders, engineers, product leads - **Explainers** — people who interpret developments clearly - **Critics / risk voices** — people who stress test hype and assumptions - **Aggregators** — useful only if they add speed or coverage without too much noise Default ordering: 1. official / primary 2. builders / operators 3. explainers 4. critics / risk voices 5. aggregators ## Quality filter Prefer sources that satisfy most of these: - close to the event - high signal-to-noise ratio - technically or operationally informed - consistent over time - not purely engagement bait - useful for decisions, not just amusement Penalize sources that are: - mostly reposting others - chronically sensational - vague and uncheckable - redundant with better primary sources ## Output patterns Choose one of these depending on the request. ### 1. Small radar list Use for users who want the minimum viable watchlist. Format: - category - source name / handle - why it matters - what to watch for Aim for 8-15 sources. ### 2. Extended source map Use when the user wants broad coverage. Format: - grouped categories - 3-8 entries per category - short note on each entry - note on which ones are must-watch vs optional ### 3. Monitoring system Use when the user wants an operational workflow. Include: - the core source list - refresh cadence - how to prune the list - how to summarize findings into notes / Notion / docs ## Maintenance rules When building a reusable source system, include these rules: - keep a **core list** and an **overflow list** - review monthly or when signal quality drops - remove duplicates aggressively - cap the default list so attention remains scarce and valuable - promote only sources that repeatedly produce useful first-order information ## AI-specific default lens When the user asks for AI information sources and gives no stronger constraint, combine: - frontier labs - open-source model players - infrastructure / hardware players - respected technical voices - skeptical / governance voices Read `references/ai-sources.md` for a starter set and selection logic. ## Tone and judgment Be opinionated. A source list is a filter, not a census. Prefer: - “Follow these 10 first” - “These 5 are optional” - “This one is noisy but useful for early chatter” Avoid pretending all sources are equally good.

path: references/ai-sources.md
content: # AI source starter set

Use this file when the user wants a high-quality AI source list, a monitoring dashboard, or a reduced watchlist from a noisy master list.

## Selection logic

Build from roles, not fame.

### 1. Official / primary sources
Use for first-order facts: launches, model updates, papers, product changes, API changes.

- OpenAI — product and model releases
- Google DeepMind — research and flagship model updates
- Anthropic — Claude, safety, API, product updates
- Meta AI — open-source model ecosystem and research
- DeepSeek — open-source / pricing / model disruption
- Alibaba Qwen — major open-source and multimodal releases
- Kimi / Moonshot — long-context and product movement in China
- MiniMax — multimodal and video movement in China
- NVIDIA / NVIDIA AI — infrastructure, hardware, and ecosystem direction

### 2. Builders / operators
Use for informed interpretation from people shipping products or research.

- Sam Altman — OpenAI strategy and market direction
- Dario Amodei — Anthropic strategy, safety, and product direction
- Demis Hassabis — DeepMind strategy and science direction
- Andrej Karpathy — technical explanation with unusually high clarity
- Yann LeCun — contrarian and anti-hype perspective from a top researcher
- Ilya Sutskever — rare but important signals on frontier research
- Jeff Dean — infrastructure and research depth
- Junyang Lin — Qwen technical direction
- Peter Steinberger — agent / developer workflow perspective

### 3. Explainers / interpreters
Use for turning scattered developments into usable understanding.

- Andrew Ng — practical trend interpretation
- Thomas Wolf — open-source ecosystem perspective
- Fei-Fei Li — spatial intelligence and broader AI direction
- Allie K. Miller — industry pattern spotting (use selectively)

### 4. Critics / risk voices
Use to test assumptions and reduce hype intoxication.

- Gary Marcus — sharp critic of overclaiming
- Eliezer Yudkowsky — extreme but important safety lens
- ethics / governance researchers when the task concerns policy or deployment risk

## Recommended small radar list

If the user wants the smallest useful default list, start with these 10:

1. OpenAI
2. Google DeepMind
3. Anthropic
4. DeepSeek
5. NVIDIA AI
6. Sam Altman
7. Andrej Karpathy
8. Dario Amodei
9. Yann LeCun
10. Gary Marcus

## Recommended China-aware expansion

Add when the user wants stronger China coverage:

- Alibaba Qwen
- Kimi / Moonshot
- MiniMax
- Bytedance / Seed-related official channels
- Junyang Lin

## Usage notes

- Prefer official accounts for “what happened?”
- Prefer builders for “why does this matter?”
- Prefer critics for “what could be wrong with this narrative?”
- Do not let aggregators dominate the list unless speed matters more than signal purity.

## Default deliverable template

Use this template unless the user asks for another format.

### Core list
- Name / handle
- Role
- Why follow
- Watch for

### Optional list
- Name / handle
- Why optional

### Pruning rule
- Remove if redundant for 30 days
- Remove if mostly reposting
- Remove if engagement bait overwhelms information value


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