source-guide

Activate when user asks where to find information at any layer, or when they are stuck and need pointers to go deeper. Always check connected personal sources first.

13 stars

Best use case

source-guide is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Activate when user asks where to find information at any layer, or when they are stuck and need pointers to go deeper. Always check connected personal sources first.

Teams using source-guide should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/source-guide/SKILL.md --create-dirs "https://raw.githubusercontent.com/ameya85/curiosity-stack/main/skills/source-guide/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/source-guide/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How source-guide Compares

Feature / Agentsource-guideStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Activate when user asks where to find information at any layer, or when they are stuck and need pointers to go deeper. Always check connected personal sources first.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Where to Look: Source Guide by Layer

## Personal Sources First

Always search connected sources before suggesting external ones. Their own notes are more relevant than anything generic.

---

## By Layer

### L1 — Mechanics
Wikipedia (technical), Arxiv.org, company engineering blogs, HackerNews, Substack (topic-specific)

### L2 — Cause Trees
Reddit (domain subreddits), HackerNews comment threads, academic survey papers, LinkedIn practitioner posts, Gartner / CB Insights

### L3 — Solution Space
ProductHunt, GitHub (topic search), TechCrunch / VentureBeat, CB Insights market maps, YouTube conference talks

### L4 — Build Requirements
LinkedIn job postings (real demand signal), earnings call transcripts, trade publications, NASSCOM / IAMAI reports, The Information

### L5 — Value Chain Actors — Global
Crunchbase, CB Insights, G2 / Capterra, LinkedIn company search

### L5 — Value Chain Actors — India
Tracxn (most comprehensive), Inc42, NASSCOM Emerge50, VCCircle, YourStory

### L6 — Research Landscape — Listed India
Screener.in, Trendlyne, Tijori Finance, BSE/NSE annual reports, concall transcripts

### L6 — Research Landscape — Unlisted / Pre-IPO India
Unlisted Arena, Planify, AngelList India, LetsVenture

---

## Building a Personal Signal System

**Daily (15–20 mins):** HackerNews front page, 2–3 domain subreddits, one newsletter

**Weekly (1–2 hours):** One deep-dive, one earnings call or conference talk, review notes

**The note principle:** Write one sentence of what you understood — not just save the link. The act of summarising forces comprehension.

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