coinhunter/references/search-workflow.md

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.