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AI Agent Workflow Collection

Skill pack
12 skills0 selected
danieltomaro13Skills in this pack

How to design and read backtests honestly — lookahead/leakage traps, point-in-time discipline, multiple comparisons, CLV vs ROI, sample size.

English

Verified bookmaker entry points (competition/event ids) for cross-book price lookups, starting with AFL.

English

Worked example of modeldevelopment for match-winner (h2h/moneyline) markets — ratings + logistic regression, home advantage, draw handling.

English

Worked example of modeldevelopment for totals (over/under) markets — scoring-process baseline, pace adjustment, holdout evaluation.

English

How to evaluate and fix probability calibration — holdout discipline, Brier/log-loss reading, Platt-style rescaling.

English

Cross-bookmaker comparison workflow — find the same selection at every book, surface the best price, and flag value.

English

DFS lineup workflow — site rules first, projections with stated sources, deterministic optimisation via optimizelineup, stacking/ownership as explicit judgment.

English

The general model-building method for ANY market — framing, sample-size discipline, feature selection (user priors + data-driven), baselines, leakage-safe validation, calibration, persistence.

English

Working definitions of the core quant concepts — Brier, log-loss, calibration, logistic regression, gradient boosting/XGBoost, regularization, walk-forward CV, CLV — and when each tool fits.

English

How to read a racecard honestly — barrier/weight/form/scratchings, converting prices to fair probability (overround/vig), cross-book best price, and exotics.

English

Interpreting captured line movement — steam vs drift, why the close is the benchmark, and how movement context changes a value report.

English

Remove the bookmaker margin (vig/overround) to estimate fair probabilities and spot value.

English

Includes Backtest Design, Book Navigation, Build a H2h Model, and other workflows.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Pack stats

Skills12CategorygeneralStars0

What’s included

Backtest Design

How to design and read backtests honestly — lookahead/leakage traps, point-in-time discipline, multiple comparisons, CLV vs ROI, sample size.

Book Navigation

Verified bookmaker entry points (competition/event ids) for cross-book price lookups, starting with AFL.

Build a H2h Model

Worked example of modeldevelopment for match-winner (h2h/moneyline) markets — ratings + logistic regression, home advantage, draw handling.

Build a Totals Model

Worked example of modeldevelopment for totals (over/under) markets — scoring-process baseline, pace adjustment, holdout evaluation.

Calibrate Probabilities

How to evaluate and fix probability calibration — holdout discipline, Brier/log-loss reading, Platt-style rescaling.

Compare Odds

Cross-bookmaker comparison workflow — find the same selection at every book, surface the best price, and flag value.

Dfs Lineup Building

DFS lineup workflow — site rules first, projections with stated sources, deterministic optimisation via optimizelineup, stacking/ownership as explicit judgment.

Model Development

The general model-building method for ANY market — framing, sample-size discipline, feature selection (user priors + data-driven), baselines, leakage-safe validation, calibration, persistence.

Quant Concepts

Working definitions of the core quant concepts — Brier, log-loss, calibration, logistic regression, gradient boosting/XGBoost, regularization, walk-forward CV, CLV — and when each tool fits.

Reading a Racecard

How to read a racecard honestly — barrier/weight/form/scratchings, converting prices to fair probability (overround/vig), cross-book best price, and exotics.

Reading Line Movement

Interpreting captured line movement — steam vs drift, why the close is the benchmark, and how movement context changes a value report.

Vig Removal

Remove the bookmaker margin (vig/overround) to estimate fair probabilities and spot value.

Quick start

  1. Choose your skills. Select individual skills above, or choose the entire pack.
  2. Copy the install prompt. Use Copy install prompt above the list.
  3. Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.

Try it with your agent

After installation, start with a request like:

Example request
Use the Backtest Design skill to help with my task.
Ask me for the context you need before getting started.

Requirements & license

  • A coding agent that can access your project files and install skills.
  • Your agent checks each skill’s instructions, dependencies, and permissions during setup.
  • Reported license for the skills shown: MIT. The author’s terms apply.