Resolution Lattice Trader
This is a template.
The default signal is cross-market inconsistency detection across deadline lattices and prerequisite chains — remix it with better parsers, richer rule extraction, or external event ontologies.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.
Strategy Overview
Most prediction bots make one-market judgments: find a market, estimate whether YES is too cheap or too expensive, then size the trade.
This skill does something else. It builds a small logical graph across related Polymarket markets and looks for violations.
Examples:
- - Temporal monotonicity: "Will X happen before June?" cannot be more likely than "Will X happen before December?"
- Prerequisite chains: "Will candidate X become president?" should not exceed "Will candidate X win the nomination?" when nomination is a necessary step.
When those relationships break, the market is not just wrong in an opinionated sense — it is internally inconsistent.
Signal Logic
Default Signal: Resolution-Lattice Inconsistency
- 1. Discover markets with structurally linked wording such as
before, by, nominee, president, approval, and similar milestone language - Parse each market question into a coarse subject plus a relation type
- Group related markets into a local graph
- Score violations of:
- earlier deadline <= later deadline
- prerequisite event >= downstream event
- 5. Trade only the leg with both:
- a real graph inconsistency
- threshold confirmation from
YES_THRESHOLD / INLINECODE6
This means the strategy is not trying to be smarter than the news. It is trying to be stricter than the market.
What Makes It Different
- - It is cross-market, not single-market
- It uses logical constraints, not only keywords or narrative bias
- It sizes conviction from inconsistency magnitude, not from raw extremeness alone
Current Constraint Families
1. Temporal Lattice
If two markets refer to the same event with different deadlines, the earlier deadline must be less likely than or equal to the later one.
If the market prices:
- -
Will X happen before June 2026? = 44% - INLINECODE8 = 37%
then the graph is broken. The strategy prefers:
- -
NO on the earlier contract if it is already expensive enough - INLINECODE10 on the later contract if it is already cheap enough
2. Prerequisite Chain
If a downstream event requires an upstream event, the downstream contract should not be more likely.
Example:
- -
Will Candidate X win the nomination? = 41% - INLINECODE12 = 53%
The graph implies:
- - nomination should not be lower than presidency
- therefore the strategy looks for
YES nomination and/or INLINECODE14
Safety & Execution Mode
The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.
| Scenario | Mode | Financial risk |
|---|
| INLINECODE17 | Paper (sim) | None |
| Cron / automaton |
Paper (sim) | None |
|
python trader.py --live | Live (polymarket) | Real USDC |
INLINECODE19 and cron: null mean nothing runs automatically until configured in Simmer UI.
Required Credentials
| Variable | Required | Notes |
|---|
| INLINECODE21 | Yes | Trading authority. Treat as a high-value credential. |
Tunables (Risk Parameters)
All declared as tunables in clawhub.json and adjustable from the Simmer UI.
| Variable | Default | Purpose |
|---|
| INLINECODE24 | INLINECODE25 | Max USDC per trade at full conviction |
| INLINECODE26 |
5 | Floor for any trade |
|
SIMMER_MIN_VOLUME |
10000 | Min market volume filter (USD) |
|
SIMMER_MAX_SPREAD |
0.07 | Max bid-ask spread |
|
SIMMER_MIN_DAYS |
3 | Min days until resolution |
|
SIMMER_MAX_POSITIONS |
6 | Max concurrent open positions |
|
SIMMER_YES_THRESHOLD |
0.38 | Buy YES only if market probability <= this value |
|
SIMMER_NO_THRESHOLD |
0.62 | Sell NO only if market probability >= this value |
Edge Thesis
Prediction markets are often analyzed as if each contract stands alone. In practice, users trade them as separate stories, while many of them are mathematically or procedurally linked. That leaves pockets where the book is not coherent.
This skill treats the market set as a probability lattice and trades the repair of that lattice.
Dependency
INLINECODE40 by Simmer Markets (SpartanLabsXyz)
- - PyPI: https://pypi.org/project/simmer-sdk/
- GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
分辨率格点交易者
这是一个模板。
默认信号是跨截止日期格点和先决条件链的跨市场不一致性检测——你可以通过更好的解析器、更丰富的规则提取或外部事件本体论对其进行重构。
该技能处理所有底层工作(市场发现、交易执行、安全防护)。你的智能体提供阿尔法收益。
策略概述
大多数预测机器人做出单一市场判断:找到一个市场,估算YES是否过于便宜或过于昂贵,然后确定交易规模。
这个技能则另辟蹊径。它在相关的Polymarket市场之间构建一个小型逻辑图,并寻找违反逻辑的情况。
示例:
- - 时间单调性:X会在六月前发生吗?的概率不应高于X会在十二月前发生吗?
- 先决条件链:候选人X会成为总统吗?的概率不应超过候选人X会赢得提名吗?——当提名是必要步骤时。
当这些关系被打破时,市场不仅在主观意义上出错——它在内部逻辑上是不一致的。
信号逻辑
默认信号:分辨率格点不一致性
- 1. 发现具有结构关联措辞的市场,如之前、之前、被提名人、总统、批准以及类似的里程碑式语言
- 将每个市场问题解析为粗略主题加关系类型
- 将相关市场分组为局部图
- 对以下违反情况进行评分:
- 较早截止日期 <= 较晚截止日期
- 先决条件事件 >= 下游事件
- 5. 仅在同时满足以下条件时进行交易:
- 存在真实的图不一致性
- 通过YES
THRESHOLD/NOTHRESHOLD的阈值确认
这意味着该策略并非试图比新闻更聪明。它试图比市场更严格。
独特之处
- - 它是跨市场的,而非单一市场
- 它使用逻辑约束,而不仅仅是关键词或叙事偏差
- 它根据不一致性幅度而非单纯的极端程度来确定信心水平
当前约束族
1. 时间格点
如果两个市场涉及同一事件但截止日期不同,则较早截止日期的概率必须小于或等于较晚截止日期。
如果市场价格为:
- - X会在2026年6月前发生吗? = 44%
- X会在2026年12月前发生吗? = 37%
那么格点就被打破了。该策略偏好:
- - 如果较早合约已经足够昂贵,则选择NO
- 如果较晚合约已经足够便宜,则选择YES
2. 先决条件链
如果下游事件需要上游事件,则下游合约的概率不应更高。
示例:
- - 候选人X会赢得提名吗? = 41%
- 候选人X会成为总统吗? = 53%
格点暗示:
- - 提名概率不应低于总统概率
- 因此策略寻找YES 提名和/或NO 总统
安全与执行模式
该技能默认为模拟交易(venue=sim)。仅在使用--live标志时进行真实交易。
| 场景 | 模式 | 财务风险 |
|---|
| python trader.py | 模拟 | 无 |
| 定时任务/自动化程序 |
模拟 | 无 |
| python trader.py --live | 实盘(Polymarket) | 真实USDC |
autostart: false和cron: null意味着在Simmer UI中配置之前,不会自动运行任何内容。
所需凭证
| 变量 | 必需 | 说明 |
|---|
| SIMMERAPIKEY | 是 | 交易授权。请视为高价值凭证。 |
可调参数(风险参数)
所有参数均在clawhub.json中声明为tunables,并可在Simmer UI中调整。
| 变量 | 默认值 | 用途 |
|---|
| SIMMERMAXPOSITION | 35 | 完全信心时每笔交易最大USDC |
| SIMMERMINTRADE |
5 | 任何交易的最低金额 |
| SIMMER
MINVOLUME | 10000 | 最低市场成交量过滤(美元) |
| SIMMER
MAXSPREAD | 0.07 | 最大买卖价差 |
| SIMMER
MINDAYS | 3 | 距结算最少天数 |
| SIMMER
MAXPOSITIONS | 6 | 最大同时持仓数量 |
| SIMMER
YESTHRESHOLD | 0.38 | 仅当市场概率 <= 此值时买入YES |
| SIMMER
NOTHRESHOLD | 0.62 | 仅当市场概率 >= 此值时卖出NO |
边缘论点
预测市场通常被分析为每个合约独立存在。实际上,用户将它们作为独立故事进行交易,而其中许多合约在数学上或程序上是相互关联的。这留下了账本不一致的漏洞。
该技能将市场集合视为概率格点,并交易该格点的修复。
依赖项
simmer-sdk by Simmer Markets (SpartanLabsXyz)
- - PyPI: https://pypi.org/project/simmer-sdk/
- GitHub: https://github.com/SpartanLabsXyz/simmer-sdk