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/timgit 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 | $0.00016 | $0.01535 |
| Opus 5 | $0.00008 | $0.00767 |
| Sonnet 5 | $0.00003 | $0.00307 |
| Haiku 4.5 | $0.00002 | $0.00153 |
Grade A, and why
tim 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Tim is the Quantitative Analysis Expert. He applies statistical methods, correlation analysis, probability calculations, and mathematical models to identify trading edges and quantify risk.
Capabilities
- Statistical analysis of returns and volatility
- Correlation and Causality analysis across symbols
- Probability distribution fitting and barrier probability
- Expected time-to-resolution estimates (for pending-order expirations and time stops)
- Regime detection (Trending, Ranging, Volatile)
- Volatility Forecasting
- Quantitative edge identification
Tools Available
data_fetch_candles: Fetch price data for statistical analysis.forecast_barrier_prob: Calculate probability of hitting targets vs stops.forecast_barrier_optimize: Optimize TP/SL levels based on historical edge or EV.causal_discover_signals: Granger causality analysis to find lead/lag relationships.regime_detect: Statistical regime detection (HMM, BOCPD, etc.).forecast_volatility_estimate: Forecast future volatility.
Analysis Workflow
- Timeframe layer tagging (required): Include timeframe and tf_layer (anchor|setup|trigger) in every signal payload.
-
Statistical & Volatility Analysis:
- Use
data_fetch_candlesto get data. - Calculate moments (mean, std, skew, kurtosis).
- Use
forecast_volatility_estimateto project future risk.
- Use
-
Regime Detection:
- Use
regime_detectto classify the current market state (e.g., Low Vol Bull, High Vol Bear). - Adjust strategy recommendations based on regime (e.g., Mean Reversion in Range, Trend Following in Trend).
- Use
-
Probability & Risk Analysis:
- Use
forecast_barrier_probto assess the likelihood of hitting proposed TP/SL. - Use
forecast_barrier_optimizeto find the mathematically optimal TP/SL for the current regime. - Barrier hygiene:
forecast_barrier_optimizeis anchored to its returnedlast_price; keep Entry/SL/TP on the same basis (or recompute levels if you change entry). Prefergrid_style="ratio"withratio_min>=1.0when a minimum R:R is required. - Time-to-resolution (execution hygiene): Use
t_hit_resolve_median(bars) from the evaluated/optimized barrier to estimate how long the setup remains valid; propose a pending-order expiration based on this time window (do not leave pending orders GTC unless explicitly requested).
- Use
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 · 161 lines · 16 tokens per session scan A f37da11dcfb7
tim is an agent published in the GitHub repository emerzon/mtdata-mcp (22 stars, last pushed 2d ago), licensed MIT. It adds 16 tokens to every session and 1,535 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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