Research Assistant
SkillCommerce & financeStructured research methodology for investigating crypto projects, protocols, market trends, and technical concepts with source evaluation and synthesis.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Research Assistant skill
What this skill tells your AI
The instructions your AI receives, as published by nirholas/three.ws in data/skills/general/research-assistant/SKILL.md and read by ahel’s review.
When to use this skill
Use when the user asks about:
- Researching a crypto topic they're unfamiliar with
- Getting a comprehensive overview of a subject
- Comparing multiple options or approaches
- Understanding a complex technical concept
- Preparing a research brief or summary
Research Methodology
1. Scope Definition
Before starting research, clarify:
- Research question: What specifically does the user want to know?
- Depth level: Surface overview, moderate analysis, or deep dive?
- Time sensitivity: Is this about current state or historical context?
- Decision context: Is this research supporting an investment, technical, or strategic decision?
- Output format: Summary paragraph, comparison table, pros/cons list, or detailed report?
2. Source Hierarchy
Prioritize information sources by reliability:
| Tier | Source Type | Trust Level | Examples |
|---|---|---|---|
| 1 | On-chain data | Highest | Block explorers, Dune Analytics, DefiLlama |
| 2 | Official documentation | High | Protocol docs, whitepapers, GitHub repos |
| 3 | Audit reports | High | Trail of Bits, OpenZeppelin, Consensys Diligence |
| 4 | Reputable analysis | Medium-High | Messari, Delphi Digital, The Block Research |
| 5 | Community research | Medium | Mirror posts, governance forums, well-known researchers |
| 6 | News outlets | Medium | CoinDesk, The Block, Blockworks |
| 7 | Social media | Low-Medium | Twitter/X threads, Reddit (verify claims independently) |
| 8 | Anonymous claims | Low | Unverified Discord/Telegram messages |
Always cross-reference claims across multiple sources.
3. Research Structure
Organize findings into these sections:
- Executive summary: 2-3 sentence answer to the research question
- Background: Context needed to understand the topic
- Key findings: Numbered list of the most important discoveries
- Analysis: Deeper examination of findings with supporting data
- Risks and limitations: What could go wrong or what is uncertain
- Conclusion: Actionable takeaway aligned with the user's decision context
4. Critical Evaluation
Apply these filters to all information:
- Recency: Is this information current? Crypto moves fast — data from 6 months ago may be outdated
- Bias check: Does the source have a financial stake? (investors talking their book, protocol teams promoting their product)
- Verifiability: Can the claim be verified on-chain or through independent sources?
- Completeness: Is the source presenting a balanced view or cherry-picking data?
- Consensus: Do multiple independent sources agree?
5. Comparison Framework
When comparing options, use a structured matrix:
| Criterion | Weight | Option A | Option B | Option C |
|---|---|---|---|---|
| [Criterion 1] | High | Score/notes | Score/notes | Score/notes |
| [Criterion 2] | Medium | Score/notes | Score/notes | Score/notes |
| [Criterion 3] | Low | Score/notes | Score/notes | Score/notes |
| Weighted result | Total | Total | Total |
6. Knowledge Gaps
Be transparent about limitations:
- Clearly state what information is unavailable or unverifiable
- Distinguish between facts, reasonable inferences, and speculation
- Flag areas where the user should do additional research
- Note when data is stale and may need refreshing
7. Output Format
- Topic: Research subject
- Summary: 2-3 sentence key finding
- Confidence level: High / Medium / Low (based on source quality and agreement)
- Key findings: Numbered list (3-7 items)
- Risks/Unknowns: What could change the conclusion
- Sources used: Brief attribution of key data points
- Recommendation: Next steps or actionable insight
Signals
- GitHub stars
- 114
- Forks
- 29
- Last commit
- Sep 2026
Advanced
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research-assistant-nirholas- Source
- github.com/nirholas/three.ws