clawby-data

# Clawby Data Analysis Fetch **real financial data** through the Clawby aggregated data API and analyze it. **The single source of truth for every interface — its params (required · format · example) and ⚠️ pitfalls — is `api/catalog/` (start at `api/catalog/_index.yaml`). Always read the relevant category yaml before calling.** The full machine catalog is `api/clawby.yaml` (server-generated, versioned). **Works with any AI agent** — Claude Code, Codex, OpenClaw, Hermes, and anything that can run shell commands or call an HTTP API: just an API key + the catalog + plain `curl`. ## Quick start ```bash # 1. Auth (once): sign in at https://www.openclawby.com/ → export CLAWBY_API_KEY=pk_xxx # 2. Find the interface in api/catalog/<category>/ (routing table below) # 3. Call it: curl -s -X POST https://api.openclawby.com/api/relay \ -H "X-API-Key: $CLAWBY_API_KEY" -H "Content-Type: application/json" \ -d '{"name":"<interface name from catalog>","params":{ ... }}' # → {source, data, credits:{remaining,used_total}} ``` ## Core workflow · Gather ALL available data first, then analyze **Completeness is the goal.** A thin answer from a single source is a failure even when correct — go broad first, analyze second. Apply this to **every** request. 1. **Turn the request into a data checklist.** Ask "what would a thorough analyst pull?" and list every relevant dimension. Over-collect on purpose (a stock → quote, short data, dark pool, options, financials, sentiment, peers; a token...