bdistill-predict
Structured Prediction Assembly
Build predictions through a disciplined 4-phase pipeline: decompose the question, extract evidence, challenge your own reasoning, then predict with calibrated confidence. Every prediction produces a portable card with full provenance.
When to use
- Make a structured forecast with evidence, not a vibes-based answer
- Binary YES/NO questions with probability (prediction markets, Polymarket, Kalshi)
- Scenario analysis ("what happens if the Fed cuts?", "will this merger close?")
- Ground predictions in your extracted KB + current web data
- Track accuracy over time with Brier scores and a resolution ledger
Input contract
required:
question: string # The prediction question ("Will the Fed cut rates before July 2026?")
domain: string # Domain slug ("macro-rates", "us-politics", "ag-commodities")
optional:
More from francyjglisboa/bdistill-skills
bdistill-extract
Extract structured, adversarially validated domain knowledge or IF-THEN decision rules from AI training knowledge. Builds a compounding knowledge base — one file per domain, deduplicated across sessions. Triggers on "extract knowledge", "build KB", "distill", "extract rules", "decision thresholds", "what do you know about". Outputs JSONL entries to {domain}.jsonl.
1bdistill-export
Export a bdistill knowledge base into any format — system prompt for Claude Projects/Cursor/Copilot/ChatGPT, Python harness module with build_prompt(), JSON for agent consumption, Excel with quality color-coding, audit checklist CSV, or fine-tuning JSONL. Triggers on "export", "system prompt", "harness", "training data", "Excel export", "export for Claude Project". Outputs file on disk.
1bdistill-xray
Probe any AI model's behavioral patterns across 6 dimensions — tool use, refusal boundaries, formatting defaults, reasoning style, persona stability, and grounding/hallucination resistance. The model probes itself, no API key needed. Generates a visual report. Triggers on "x-ray", "probe behavior", "behavioral analysis", "model evaluation", "how does this model behave". Outputs behavioral profile with scores.
1bdistill-operationalize
Connect exported rules to live data for automated monitoring. Loads a bdistill rules export, fetches current data from free APIs or local feeds, contrasts each rule's conditions against reality, and reports which rules triggered with current values and impact estimates. Works with any domain — weather, market, compliance, clinical. Triggers on "operationalize", "monitor", "check against live data", "contrast rules", "what's triggered". Outputs decision report.
1bdistill-validate
Detect confabulated claims by re-asking entries with rephrased questions and measuring variance — both numeric stability (do the numbers stay the same?) and structural stability (do the conditions, scope, and reasoning stay the same?). Use after bdistill-extract to filter your KB before export. Triggers on "validate KB", "consistency check", "are these numbers real", "verify thresholds", "detect hallucination", "stability check". Outputs stability scores per entry.
1bdistill-abstract
Extract structural rules from one domain, abstract to bare skeletons at three granularity levels, then re-instantiate in other domains to discover non-obvious cross-domain correspondences. Filters with mandatory web-grounded novelty check AND adversarial validity challenge AND reverse round-trip validation. Triggers on "abstract rules", "cross-domain", "structural analogy", "what pattern in X applies to Y", "transfer rules between domains". Outputs validated cross-domain rule correspondences with structured testable predictions.
1