Simple Functions
GLOSSARY/ANALYSIS

Evaluation Cycle

An evaluation cycle is the automated process by which the agent reviews new signals, updates causal tree probabilities, recalculates edge, and determines whether any strategy conditions are met.

CLI:sf thesis evaluate

The Heartbeat Evaluation Loop

The evaluation cycle is the agent's core loop. It runs on a schedule (the "heartbeat") and on-demand when important signals arrive.

What Happens in Each Cycle

  1. Signal ingestion: Collect new signals since the last evaluation — news articles, price changes, user notes, webhook data
  2. Node mapping: Map each signal to the relevant causal tree node(s)
  3. Probability update: Adjust node probabilities based on new information
  4. Root recomputation: Cascade updates through the tree to compute new thesis-implied prices
  5. Edge calculation: Compare updated thesis prices against current market prices
  6. Strategy evaluation: Check if any strategy entry/exit/stop conditions are now met
  7. Notification: Send alerts for significant changes (edge found, confidence shift, strategy trigger)

Evaluation Frequency

  • Scheduled: Every 30-60 minutes during market hours
  • Event-triggered: Immediately when a high-priority signal arrives (e.g., economic data release)
  • Manual: You can force an evaluation with sf thesis evaluate

What the Agent Produces

Each evaluation generates:

  • Updated confidence score and delta (e.g., "confidence changed from 68% to 72%")
  • Summary of what changed and why
  • Updated edge snapshot across all linked markets
  • Any triggered strategy actions

Evaluation History

All evaluations are stored as an append-only log. You can review past evaluations to understand how your thesis evolved over time and whether the agent's updates were accurate.

Example

sf thesis evaluate

Evaluation #47 for "US Recession by 2026"
  Signals processed: 3
    • BLS: February unemployment rate 4.8% (was 4.5%)
    • Reuters: Consumer confidence index drops to 88.3
    • Kalshi: KXRECSSNBER-26 moved from 28¢ to 30¢

  Node updates:
    n1.1: Unemployment > 5%     35% → 42%  (BLS data)
    n2.2: Consumer confidence < 80   48% → 52%  (confidence data)

  Thesis confidence: 68% → 72% (+4pt)
  Root probability:  38% → 42% (+4pt)

  Edge changes:
    KXRECSSNBER-26: +10pt → +12pt  (market moved +2¢ but thesis moved +4pt)

  Strategy check:
    S-001: Entry condition met (edge > 10pt, price < 32¢) ✓
    Action: Recommend buy 50 contracts at $0.30

Related Terms

Causal Tree

A causal tree is a structured probabilistic model that breaks down a complex event into a hierarchy of independent, verifiable sub-conditions. Each node has a probability, and the tree computes the overall probability of the root event.

Thesis

A thesis is a structured investment argument that combines a directional view, a causal model of why the view is correct, and specific market positions that express the view. In SimpleFunctions, a thesis is the core unit of analysis.

Heartbeat

The heartbeat is the automated monitoring engine that periodically scans for new information, runs evaluation cycles, and triggers strategy actions. It keeps your thesis alive and responsive 24/7.

Signal

A signal is any piece of new information that could affect a thesis — a news article, a price movement, a data release, a user note, or an external webhook event. The agent evaluates signals against the causal tree.

Edge Detection

Edge detection is the systematic process of scanning prediction markets to find contracts where the market price diverges from your thesis-implied fair value by more than the cost of execution.

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