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How to use the Alpha Lab client in Wayfinder Paths for discovering alpha insights — scored tweets, chain flows, top APYs, and delta-neutral opportunities.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
How to use the Delta Lab client (DELTA_LAB_CLIENT) for basis APY discovery, delta-neutral pair finding, lending/perp/price screening, time-series, and opportunity analysis across protocols. TRIGGER when the user asks about yields, APYs, basis, funding, delta-neutral, top-apy, lending rates, perp funding, borrow routes, or opportunity screening; OR when writing/editing a script that imports `DELTA_LAB_CLIENT` or uses `research_*` MCP tools; OR before any yield/basis/funding research. The MCP surface is intentionally narrow (snapshots only) — anything time-series, by-asset-id, plotting, or bulk requires the Python client documented here.
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| name | using-alpha-lab |
| description | How to use the Alpha Lab client in Wayfinder Paths for discovering alpha insights — scored tweets, chain flows, top APYs, and delta-neutral opportunities. |
| metadata | {"tags":"wayfinder, alpha-lab, alpha, insights, twitter, chain-flows"} |
Alpha Lab = Scored alpha insight feed
from wayfinder_paths.core.clients.AlphaLabClient import ALPHA_LAB_CLIENT
# Search all insights (sorted by score)
await ALPHA_LAB_CLIENT.search()
# Filter by type
await ALPHA_LAB_CLIENT.search(scan_type="twitter_post", min_score=0.7)
# Text search
await ALPHA_LAB_CLIENT.search(search="ETH funding", limit=10)
# List available scan types
await ALPHA_LAB_CLIENT.get_types()
MCP quick access:
research_search_alpha(limit="20") # Top 20 insights
research_search_alpha(scan_type="twitter_post", limit="10") # Top 10 tweets
research_search_alpha(query="ETH", limit="10") # Search "ETH"
research_search_alpha(created_after="2026-03-06T00:00:00Z", limit="20") # Today's insights
research_get_alpha_types() # List scan types
Tool args: research_search_alpha(query, scan_type, created_after, created_before, limit)
query: text search, _ for none (default _)scan_type: filter by type, all for none (default all)created_after / created_before: ISO 8601 datetime bounds, _ to skip (default _)limit: max results (default "20", max "200")Critical gotchas:
data = await ALPHA_LAB_CLIENT.search()offset for pagination (Python client only)Alpha Lab is self-contained for alpha requests. It already includes delta_lab_top_apy and delta_lab_best_delta_neutral scan types, so do NOT also query Delta Lab separately. Only use Delta Lab directly when the user asks for raw rates, historical timeseries, or detailed screening — not for "today's alpha".