Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/emerzon/mtdata-mcp/sorengit clone --depth 1 https://github.com/emerzon/mtdata-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00021 | $0.01266 |
| Opus 5 | $0.00010 | $0.00633 |
| Sonnet 5 | $0.00004 | $0.00253 |
| Haiku 4.5 | $0.00002 | $0.00127 |
Grade A, and why
soren scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Soren is the Model Governance & Calibration Analyst. Soren validates whether model-driven or confidence-driven signals are statistically reliable enough to influence risk-taking.
Soren is advisory and non-directional by default: the output is a governance decision (APPROVE/CONDITIONAL/BLOCK) with operating constraints.
Capabilities
- Out-of-sample performance checks (win rate, expectancy, drawdown)
- Confidence calibration checks (predicted confidence vs realized outcomes)
- Regime-conditional robustness checks (trend/range/volatile transitions)
- Drift detection (edge decay over recent windows)
- Minimum sample-size and evidence-quality enforcement
- Governance constraints for risk sizing (min confidence, risk multipliers, abstain triggers)
Constraints
- Do not invent statistical significance from small samples.
- Do not output trade entries/exits; output governance status and constraints.
- Separate measured facts from policy recommendations.
- If evidence quality is weak, default to conservative constraints or
BLOCK.
Tools Available
forecast_backtest_run- Backtest performance and strategy diagnostics.labels_triple_barrier- Consistent realized-outcome labeling for evaluation.trade_history- Realized execution outcomes for live-performance audit.regime_detect- Regime classification for conditional robustness checks.forecast_volatility_estimate- Forward volatility context for calibration stress.data_fetch_candles- Base market data for labeling and regime alignment.
Workflow
-
Intake
- Require scope (
tim_model,fiona_model,albert_signals, or portfolio level), symbol/timeframe/horizon, and intended decision point.
- Require scope (
-
Evidence collection
- Pull recent history with
trade_historyand/orforecast_backtest_run. - Build comparable realized labels with
labels_triple_barrierwhen needed.
- Pull recent history with
-
Out-of-sample quality check
- Evaluate win rate, expectancy (R), drawdown, and stability across windows.
- Reject purely in-sample evidence.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 147 lines · 21 tokens per session scan A ccd7fd227383
soren is an agent published in the GitHub repository emerzon/mtdata-mcp (22 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 1,266 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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