Results for “statistical-arbitrage”

Detect and evaluate arbitrage opportunities across sportsbooks and prediction markets. Calculate guaranteed-profit scenarios, middle bets, and cross-platform price discrepancies. Use when comparing odds across books, calculating arb percentages, evaluating middle opportunities, or building odds-comparison workflows. Also trigger for 'arb bet', 'sure bet', 'arbitrage', 'odds comparison', 'middle bet', 'risk-free bet', or 'line shopping'.

Find and analyze arbitrage opportunities across prediction markets like Polymarket and Kalshi. Use when you need to match equivalent markets, compare prices, and verify whether a spread looks actionable.

Find arbitrage opportunities across Polymarket and Kalshi prediction markets via AIsa API. Scan sports markets for cross-platform price discrepancies, compare real-time odds, verify orderbook liquidity. Use when user asks about: prediction market arbitrage, cross-platform price differences, sports betting arbitrage, odds comparison, risk-free profit, market inefficiencies.

The Sovereign Litigation Protocol (SLP-2026). A recursive, high-fidelity framework for autonomous advocacy, multi-jurisdictional discovery, and the algorithmic resolution of civil and commercial disputes.

Deposit Base USDC into PMFI pARBITRAGE vault for prediction market arbitrage exposure, and withdraw pARB back to USDC through Bankr.

Use when selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.

Use with analysis-agent or task-agent for task-local transaction, isolation, and conflict decisions. Do not use without a transaction decision or as task owner.

Use to design or audit a QA dispute and appeal workflow with timeboxes, adjudication standards, and second-level consistency so appeals improve trust instead of rewriting scores without rules. Trigger for "QA appeal process", "agents disputing scores", "who adjudicates QA disputes", "overturn rate too high", second-level review standards, or calibration erosion from ad-hoc score changes.

Audits decisions and situations for operating psychological biases using Munger's 25 tendencies framework, producing a structured analysis with countermeasures.

Prüft Auditrechte-Klauseln in AGBs: ordnet Sachverhalt, Normen, Beweislast und Gegenargumente, liefert eine Fristen- und Risikoampel mit Sofortschritten und erstellt Redline-Entwürfe.

ADR Fleet

Prediction market arbitrage & alpha scout. Searches Polymarket and Kalshi for the same event, runs cross-platform arb math (including fees), and ranks opportunities by profitability. Use when asked to "find arb", "scout markets", "find edge", or scan a specific topic across prediction markets.

Selects a minimal, non-redundant set of facts, artifacts, skills, and references for a working decision when context is stale, uncertain, or over budget.

Computes the SQuAD metric using torchmetrics, given predictions and ground truth. Use when evaluating question-answering outputs with exact match and F1 scores.

通过 AIsa API 发现 Polymarket 和 Kalshi 预测市场的套利机会。扫描体育市场跨平台价差、比较实时赔率、验证订单簿流动性。适用场景：预测市场套利、跨平台价差、体育博彩套利、赔率对比、无风险利润、市场低效。 Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

Evaluates an AI judge system's pairwise ranking accuracy on generated commit messages against a heuristic ground truth from five automatic text metrics, using the MCMD dataset.

Score a clinical ASR manifest against a chosen NIM, produce a five-section KER leaderboard, and route the user via a post-eval decision tree.

Orchestrate token-heavy research, coding, and testing by delegating bounded tasks to cheaper subagents while reserving Claude Fable for architecture, synthesis, and final review.

Judges agent outputs against LaRuche's quality standards, returning a structured scorecard with scores, verdict, and actionable corrections.

TRAK: Attributing Model Behavior at Scale

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Compares prediction market probabilities from Polymarket with options-implied probabilities to identify mispricing signals and potential arbitrage opportunities.

`analysis-agent`/`task-agent`/`review-agent`: primary-Skill-selected for races, locks, optimistic conflicts, or worker overlap; never task owner; skip without concurrency impact.

`analysis-agent`/`task-agent`: use when a use case coordinates authorization, domain work, transactions, or external effects; skip transport, storage, and rule-only work.

Recommend model families and validation strategy based on data, constraints, and objective. Use when: (1) choosing algorithms, (2) balancing bias/variance, (3) planning benchmark baselines. NOT for: final legal/compliance sign-off.

Evaluates social bias in question-answering models using the BBQ benchmark, measuring accuracy and a bias score across ambiguous and disambiguated contexts to reveal reliance on stereotypes.

`analysis-agent`/`task-agent`/`review-agent`: use when latency, throughput, bundle, memory, CPU, query, rendering, or resource cost needs a budget; skip without performance risk.

Use to audit how payment disputes, chargebacks and unrecognised-transaction claims are handled against scheme deadlines and evidence standards. Trigger for "audit our dispute handling", "chargeback quality review", "are we meeting scheme deadlines", unrecognised transaction claims, provisional credit decisions, or a customer complaining their dispute was rejected unfairly.

当需要在众多机会中筛选出投入产出比最高的选项，以最小化风险并最大化潜在回报时

Benchmarks language model agents on the C2C multi-agent negotiation task, reporting win rate across starting positions.

The choice is not about scale or sophistication.

Lightweight ContentShake AI self-check the /draft stage can call before saving. Returns just SEO + Quality scores (no full optimization) so the writer knows whether the draft is in winning territory before /quality-check runs. Fails soft when SEMRUSH_API_KEY is unset.

Aikido Findings Triage Workflow

Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations.

Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms.