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coinhunter/references/search-workflow.md

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# Search Workflow
Use this workflow when the user wants you to proactively discover meme-coin / 妖币 candidates instead of analyzing a known ticker.
## Goal
Produce a shortlist with enough evidence to answer:
- what deserves attention now
- what is merely noisy
- what should be avoided
## Default search strategy
Unless the user specifies otherwise, search for **liquid speculative candidates** first and avoid ultra-microcaps.
Run search in this order:
1. **Theme scan**
- Search current meme-coin themes by chain or narrative
- Examples:
- `Solana meme coins trending`
- `Base meme coin watchlist`
- `AI meme coin trending`
- `new meme coin listed today`
2. **Candidate extraction**
- Pull out repeated names that appear across multiple sources
- Prefer coins that appear in both market-oriented and community-oriented sources
3. **Candidate verification**
- For each candidate, search:
- `<coin> market cap liquidity`
- `<coin> holders tokenomics`
- `<coin> rug risk`
- `<coin> listed on exchange`
4. **Cross-check timing**
- Search whether the coin is already broadly saturated:
- `<coin> trending X`
- `<coin> breakout volume`
- `<coin> price surge`
- If it is already universally discussed, consider classifying it as late rather than early
## Source preference
Prefer a mix of:
- credible exchange announcements or listing pages
- market data summaries
- crypto news aggregation
- community/trading discussion summaries
Do not rely entirely on project websites or obvious promotion pages.
## Discovery rules
### Good candidate signs during search
- name appears repeatedly across different sources
- tied to a live narrative or active chain
- discussion suggests recent acceleration, not just old fame
- accessible enough that the user can realistically trade it
### Weak candidate signs during search
- only appears in promotional pages
- only appears on tiny venues
- no independent discussion or market data context
- most results are already about an explosive move that happened days ago
## Shortlist size
Default to **3-5 candidates**.
If the search returns many names:
- keep the most repeated
- keep the ones with the clearest narrative
- remove obviously illiquid or scammy names first
## Output shape for discovery mode
For each shortlisted candidate include:
- ticker / name
- chain / venue context if known
- why it entered the shortlist
- biggest risk
- tentative bucket: candidate runner / watch-only / avoid
Then give a final rank order.
## Notes
When evidence is weak, say so. Discovery mode is for narrowing attention, not pretending certainty.