get_backtest_tuning_state

shallow

io.github.wnsod/oneqaz-trading-mcp · Verify this server

Purpose: Continuous self-calibration evidence. Each entry shows the auto-tuned lag_hours and sensitivity per cell, derived from real backtest outcomes. Proves the system adapts to measured reality rather than static heuristics. Triggers (casual questions too): "does the system self-correct?", "시스템이 스스로 보정해?", "how is it calibrated?", "튜닝 상태 보여줘", "is it adapting to what actually happened?". When to call: after get_prediction_accuracy, to show the system updates itself. Prerequisites: get_prediction_accuracy recommended for context. Next steps: get_monthly_accuracy_trend. Caveats: `last_backtest` timestamp indicates tuning freshness. Args: category: Optional category filter target_market: Optional target market filter Disclaimer: Information only, not investment advice.

100.0/100

1 trials · measured 8 days ago

get_backtest_tuning_state scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.wnsod/oneqaz-trading-mcp, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote + stdio
Credential class
open
Category
Finance & compliance
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: get_backtest_tuning_state
[![Vouch score](https://vouch.tools/api/tools/a98ec336-3079-4898-8294-5f550cb4cd63/badge.svg)](https://vouch.tools/tools/a98ec336-3079-4898-8294-5f550cb4cd63)
get_backtest_tuning_state — Vouch