# Polymarket Liquidity Mm

> Dual-sided market making with automated inventory skew balancing and capital recycling via position merging

- Skill: `knuckles-team/polymarket-liquidity-mm` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add knuckles-team/polymarket-liquidity-mm`
- Raw SKILL.md: https://api.skillmd.com/api/skills/knuckles-team/polymarket-liquidity-mm/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: Knuckles-Team (https://skillmd.com/u/knuckles-team)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/knuckles-team/polymarket-liquidity-mm

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# polymarket-liquidity-mm Workflow

Dual-sided market making with automated inventory skew balancing and capital recycling via position merging

### Step 0: mcp_market_data
Monitor target market orderbook depth and calculate best bid/ask spreads
Expected: bid_ask_depth

### Step 1: mcp_portfolio [depends_on: Step 0]
Analyze active token inventory and portfolio balance ratio
Expected: inventory_weight

### Step 2: mcp_risk [depends_on: Step 1]
Compute inventory skew quoting offsets (lower ask if long, higher bid if short)
Expected: quoting_price_offsets

### Step 3: place-market-making-orders [skill: mcp_orders] [depends_on: Step 2]
Place dual-sided limit orders on target market to capture spread
Expected: dual_limit_orders

### Step 4: refresh-market-making-orders [skill: mcp_orders] [depends_on: Step 3]
Cancel stale or out-of-range quotes and dynamically adjust offsets based on volatility
Expected: updated_market_making_state

## Execution

Run this workflow as a dependency-ordered DAG. Steps with no unmet `depends_on` run in parallel; dependents run after their prerequisites complete.

- **Run first (in parallel):** Step 0 — mcp_market_data
- **After level 0:** Step 1 — mcp_portfolio
- **After level 1:** Step 2 — mcp_risk
- **After level 2:** Step 3 — place-market-making-orders
- **After level 3:** Step 4 — refresh-market-making-orders

**Execution:** If graph-os is reachable, offload the whole DAG via `graph_orchestrate action=execute_workflow` (or the `kg-delegate` skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet `depends_on` in parallel, then their dependents.