# Using Alpha Lab

> How to use the Alpha Lab client in Wayfinder Paths for discovering alpha insights — scored tweets, chain flows, top APYs, and delta-neutral opportunities.

- Skill: `wayfinderfoundation/using-alpha-lab` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds add wayfinderfoundation/using-alpha-lab`
- Raw SKILL.md: https://api.skillmd.com/api/skills/wayfinderfoundation/using-alpha-lab/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: WayfinderFoundation (https://skillmd.com/u/wayfinderfoundation)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/wayfinderfoundation/using-alpha-lab

---


## What you need to know (TL;DR)

**Alpha Lab = Scored alpha insight feed**

```python
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_search_alpha(sort="-created", limit="20")                                 # Newest insights
research_get_alpha_types()                                                         # List scan types
```

Tool args: `research_search_alpha(query, scan_type, created_after, created_before, sort, 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 `_`)
- `sort`: `-insightfulness_score` (default) or `-created` for newest first
- `limit`: max results (default `"20"`, max `"200"`)

**Critical gotchas:**
- Client returns data directly (not tuples) — `data = await ALPHA_LAB_CLIENT.search()`
- Scores are 0-1 floats (1 = most insightful)
- Default sort is score descending — all-time top scorers, NOT newest. For "latest/fresh alpha" pass `sort="-created"` (or a `created_after` bound), or recent items stay invisible unless they crack the all-time top N and the feed looks stale
- Max 200 results per call; use `offset` for pagination (Python client only)

## When to use

- "What's the latest alpha?" / "Show me today's insights"
- "Any interesting tweets about ETH?"
- "What chain flows are happening?"
- "What are the highest-scored insights?"

**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".

## How to use

- [rules/what-is-alpha-lab.md](rules/what-is-alpha-lab.md) - What Alpha Lab is and its scan types
- [rules/high-value-reads.md](rules/high-value-reads.md) - Core queries and MCP URIs
- [rules/response-structures.md](rules/response-structures.md) - Response shapes
- [rules/gotchas.md](rules/gotchas.md) - Common mistakes