Polymarket Bundle Cs2 Maps Trader

v0.0.2

Trades CS2 BO3 Winner markets when individual map winner probabilities imply a different BO3 outcome on Polymarket. Uses the binomial BO3 model to calculate...

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Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Polymarket Bundle Cs2 Maps Trader" (diagnostikon/polymarket-bundle-cs2-maps-trader) from ClawHub.
Skill page: https://clawhub.ai/diagnostikon/polymarket-bundle-cs2-maps-trader
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

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OpenClaw CLI

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openclaw skills install polymarket-bundle-cs2-maps-trader

ClawHub CLI

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npx clawhub@latest install polymarket-bundle-cs2-maps-trader
Security Scan
Capability signals
CryptoRequires sensitive credentials
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
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medium confidence
Purpose & Capability
The skill claims to trade Polymarket BO3 markets and the code, dependency (simmer-sdk), and SKILL.md all implement that purpose. However, the registry header in the submission stated "Required env vars: none" and "Primary credential: none", which contradicts clawhub.json and the SKILL.md that both require SIMMER_API_KEY. The credential requirement itself is appropriate for a trading client, but the metadata mismatch is an inconsistency the publisher should fix.
Instruction Scope
SKILL.md and trader.py instruct the agent to discover markets, build map/BO3 bundles, compute binomial-implied probabilities, and place trades. The skill defaults to paper trading and requires an explicit --live flag for real trades. The instructions do not direct reading unrelated system files or exfiltrating data beyond the trading API; optional 'remix' suggestions mention other external APIs only as optional enhancements.
Install Mechanism
No custom install script is present. clawhub.json lists a pip dependency on 'simmer-sdk' (PyPI) with a GitHub repository link; this is a standard package install path. There are no downloads from untrusted URLs or archive extracts in the submission. You should still audit the simmer-sdk package source before granting credentials.
Credentials
The skill requires SIMMER_API_KEY and reads a set of tunable environment variables for sizing/filters. Those environment variables are proportional to a trading bot. The inconsistency to flag is that the registry summary reported no required env vars while both clawhub.json and SKILL.md declare SIMMER_API_KEY as required — this mismatch should be corrected by the author. No other unrelated secrets are requested.
Persistence & Privilege
The skill is not marked always:true and autostart is false, so it will not force-run on every agent. clawhub.json marks the automaton entrypoint as trader.py (managed=true) but with autostart disabled; the skill can be run when explicitly invoked. Autonomous invocation (disable-model-invocation=false) is the platform default and is not alone a red flag here.
Assessment
This skill appears to do what it says: it uses the Simmer SDK to read Polymarket markets and place trades using a binomial model, and it defaults to paper trading unless you pass --live. Before you run it with real funds: (1) Verify the source/author (owner is listed as Diagnostikon but no homepage was provided). (2) Inspect the simmer-sdk package on PyPI/GitHub to ensure it is legitimate and review what network endpoints it calls. (3) Only provide a SIMMER_API_KEY with least privilege necessary and be prepared to rotate it. (4) Test extensively in paper mode and review logs for unexpected network activity. (5) Ask the publisher to fix the registry metadata that currently omits the required SIMMER_API_KEY so the manifest accurately reflects credentials the skill needs.

Like a lobster shell, security has layers — review code before you run it.

latestvk97fm8yd75f7zstw82y2jwzw9s853bgd
141downloads
0stars
3versions
Updated 1w ago
v0.0.2
MIT-0

Bundle -- CS2 Maps BO3 Arbitrage Trader

This is a template. The default signal detects inconsistencies between individual CS2 map winner probabilities and the BO3 match winner market -- remix it with team Elo ratings, map pool veto data, or live scoreboard feeds. The skill handles all the plumbing (market discovery, bundle construction, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

CS2 matches on Polymarket list separate markets for each map winner and the overall BO3 winner:

  • "Counter-Strike: NAVI vs FaZe - Map 1 Winner" = 55% (NAVI)
  • "Counter-Strike: NAVI vs FaZe - Map 2 Winner" = 60% (NAVI)
  • "Counter-Strike: NAVI vs FaZe - Map 3 Winner" = 50% (NAVI)
  • "Counter-Strike: NAVI vs FaZe (BO3) - IEM Katowice" = 58% (NAVI)

The individual map probabilities constrain the BO3 probability via the binomial model. When they don't match, the BO3 market is mispriced.

Edge

P(BO3 win) must equal P(win M1)*P(win M2) + P(win M1)*P(lose M2)*P(win M3) + P(lose M1)*P(win M2)*P(win M3). Retail traders price the BO3 market independently from individual maps, creating structural mispricings that this skill exploits.

Signal Logic

  1. Discover CS2 markets via get_markets(limit=200) as primary + keyword search fallback
  2. Parse each question: extract (match_key, map_number, team_a, team_b) for map winners
  3. Parse BO3 winner markets: extract (match_key, team_a, team_b)
  4. Group into match bundles: one BO3 market + its individual map markets
  5. For each bundle with at least Map 1 + Map 2 + BO3 winner:
    • Calculate implied BO3 probability from map probabilities (binomial model)
    • If Map 3 market exists, use its probability; otherwise assume 0.5
    • Compare implied vs actual BO3 market probability
    • If difference > MIN_VIOLATION: trade the BO3 market toward map-implied probability
  6. Size by conviction (CLAUDE.md formula), not flat amount

Remix Signal Ideas

  • HLTV Elo ratings: Pull team ratings and recent head-to-head records -- teams with map pool advantages create asymmetric Map 3 probabilities that the default 0.5 assumption misses
  • Map veto prediction: Use historical veto patterns to predict which maps will be played -- if a team always bans Inferno, the Map 3 probability on Inferno should be different from Mirage
  • Live scoreboard data (PandaScore API): Stream real-time round scores during Map 1 -- if one team is dominating, Map 2 and BO3 probabilities should shift before the market adjusts
  • Map-specific win rates: Fetch team win rates on specific maps from HLTV -- if FaZe has 70% win rate on Nuke but the market prices Map 2 at 55%, that is an additional edge layer

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

ScenarioModeFinancial risk
python trader.pyPaper (sim)None
Cron / automatonPaper (sim)None
python trader.py --liveLive (polymarket)Real USDC

autostart: false and cron: null mean nothing runs automatically until configured in Simmer UI.

Required Credentials

VariableRequiredNotes
SIMMER_API_KEYYesTrading authority. Treat as a high-value credential.

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

VariableDefaultPurpose
SIMMER_MAX_POSITION40Max USDC per trade at full conviction
SIMMER_MIN_TRADE5Floor for any trade
SIMMER_MIN_VOLUME5000Min market volume filter (USD)
SIMMER_MAX_SPREAD0.08Max bid-ask spread
SIMMER_MIN_DAYS0Min days until resolution (0 = allow same-day)
SIMMER_MAX_POSITIONS8Max concurrent open positions
SIMMER_YES_THRESHOLD0.38Buy YES only if market probability <= this
SIMMER_NO_THRESHOLD0.62Sell NO only if market probability >= this
SIMMER_MIN_VIOLATION0.05Min implied-vs-actual BO3 probability difference to trade

Edge Thesis

Traditional sportsbooks employ quantitative models that enforce consistency between individual game prices and series prices. Polymarket has no such mechanism -- each market is priced by its own order book. CS2 BO3 markets are particularly vulnerable because:

  • Individual map markets attract map-specific bettors who don't consider the BO3 implication
  • BO3 markets attract series-level bettors who don't decompose into individual maps
  • Map 3 probability is often unknown or assumed at 50%, creating systematic errors
  • Live match flow on Map 1 shifts map probabilities before the BO3 market adjusts
  • Tournament format changes (upper/lower bracket) affect team motivation asymmetrically across maps
  • The binomial constraint is mathematical -- map probabilities must sum correctly to produce the BO3 probability

This skill treats the map winner probabilities as inputs to a binomial model and trades the BO3 market when it diverges from the model's output.

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

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