v1.0.0 to v1.0.0

22 added, 30 removed. Audit A to A.

---

name: dispatch

- description: "Routes sports analytics requests to the right 2-3 skills. Load this FIRST when a sports data or analytics request comes in and you are unsure which skills to activate. Prevents loading all 30 skills when only 2-3 are needed. Also handles first-use persona detection."

+ description: "Routes hockey analytics requests to the right 2-3 skills. Load this FIRST when a hockey data or analytics request comes in and you are unsure which skills to activate. Prevents loading all 28 skills when only 2-3 are needed. Also handles first-use persona detection."

metadata:

version: 1.0.0

- author: Sports Data HQ

+ author: PuckAPI

---

# Skill Dispatch Guide

- When a sports analytics request comes in, match it to a pattern below. Load those skills. Don't load everything.

+ When a hockey analytics request comes in, match it to a pattern below. Load those skills. Don't load everything.

- **Default data tool:** `sportsdatahq-tool` -- covers most data needs. Load it alongside the relevant strategy skill unless the request specifically needs a different tool.

+ **Default data tool:** `puckapi-tool` -- covers most data needs. Load it alongside the relevant strategy skill unless the request specifically needs a different tool.

---

## First-Use Persona Detection

On first interaction, identify which path the user is on:

| Signal | Persona | Start With |

|--------|---------|-----------|

- | "What games are tonight?" / exploring data | **Explorer** | `game-lookup` + `sportsdatahq-tool` |

+ | "What games are tonight?" / exploring data | **Explorer** | `game-lookup` + `puckapi-tool` |

| "Help me build a model" / "I want to predict" | **Builder** | `hockey-analytics` + `feature-engineering` |

| "What are tonight's best bets?" / "Give me picks" | **Daily User** | `daily-card` + `odds-explorer` |

| "I have a model, is it any good?" | **Validator** | `walk-forward-validation` + `probability-calibration` |

| "I'm new to hockey analytics" | **Learner** | `hockey-analytics` + `ai-sports-workflow` |

- | "NFL analysis" / "EPA" / "fourth down" | **NFL Analyst** | `epa-situational-query` + `fourth-down-decision` |

+ | "I'm new to betting" | **New Bettor** | `odds-analysis` + `edge-detection` |

---

## Request Patterns -> Skills to Load

### "Who plays tonight?" / "What's the schedule?" / "Game results"

1. `game-lookup` -- find games by date, team, season

- 2. `sportsdatahq-tool` -- `get_games`, `get_schedule` endpoints

+ 2. `puckapi-tool` -- `get_games`, `get_schedule` endpoints

### "How are the Sabres doing?" / "Standings" / "Team stats"

1. `team-analysis` -- standings, stats, rankings, SOS

- 2. `sportsdatahq-tool` -- `get_standings`, `get_team_stats`

+ 2. `puckapi-tool` -- `get_standings`, `get_team_stats`

### "Tell me about Connor McDavid" / "Player stats" / "Compare players"

1. `player-scouting` -- search, stats, comparison, NHLe

- 2. `sportsdatahq-tool` -- `search_players`, `get_player_stats`

+ 2. `puckapi-tool` -- `search_players`, `get_player_stats`

### "Who's starting in goal?" / "Goalie matchup" / "Save percentage"

1. `goalie-analysis` -- leaderboard, workload, xG-adjusted metrics

- 2. `sportsdatahq-tool` -- `get_goalie_stats`

+ 2. `puckapi-tool` -- `get_goalie_stats`

### "What are the odds?" / "Line shopping" / "Best price"

1. `odds-explorer` -- multi-book comparison, line movement

- 2. `sportsdatahq-tool` -- `get_odds`, `get_line_movement`

+ 2. `puckapi-tool` -- `get_odds`, `get_line_movement`

3. For odds math/devigging: also load `odds-analysis`

### "Show me games where..." / "Find all teams that..." / natural language query

1. `nl-to-query` -- translate natural language to structured queries

- 2. `sportsdatahq-tool` -- routes to appropriate endpoint

+ 2. `puckapi-tool` -- routes to appropriate endpoint

3. If pattern found: `ai-sports-workflow` for follow-up hypothesis testing

### "What is Corsi?" / "Explain xG" / "Hockey analytics basics"

1. `hockey-analytics` -- metric definitions, formulas, context

- 2. `sportsdatahq-tool` -- pull real data to demonstrate

+ 2. `puckapi-tool` -- pull real data to demonstrate

### "How do I use Claude for sports analysis?" / "What questions should I ask?"

1. `ai-sports-workflow` -- prompt patterns, hypothesis testing, iteration

2. Load relevant data skill based on the specific question

### "How do I automate this?" / "Run daily" / "Pipeline"

1. `data-pipeline` -- GitHub Actions, scheduling, model versioning

- 2. Reference `sportsdatahq-tool` for endpoint costs in automation budget

+ 2. Reference `puckapi-tool` for endpoint costs in automation budget

### "Help me build features" / "Feature engineering" / "What features should I use?"

1. `feature-engineering` -- rolling windows, leakage detection, shift(1)

- 2. `sportsdatahq-tool` -- historical data endpoints

+ 2. `puckapi-tool` -- historical data endpoints

3. If user is new to metrics: also load `hockey-analytics`

### "How do I validate my model?" / "Is k-fold okay?" / "Cross-validation"

1. `walk-forward-validation` -- temporal CV, anti-leakage, significance testing

2. If user has a model: `probability-calibration` for probability verification

### "Help me build a prediction model" / "Train a model" / "XGBoost"

1. `model-building` -- model selection, training, evaluation

2. `walk-forward-validation` -- correct evaluation method

3. `feature-engineering` -- if features aren't built yet

### "Build an Elo rating system" / "Rating system" / "Team ratings"

1. `elo-engineering` -- 5 variants, tuning, carryover

- 2. `sportsdatahq-tool` -- `get_games` for historical results

+ 2. `puckapi-tool` -- `get_games` for historical results

### "Are my probabilities calibrated?" / "Platt scaling" / "Brier score"

1. `probability-calibration` -- reliability diagrams, scaling methods

2. If model outputs available: proceed directly

3. If not: route to `model-building` first

### "How do I devig odds?" / "Implied probability" / "Shin method"

1. `odds-analysis` -- conversion, devigging, no-vig lines

- 2. `sportsdatahq-tool` -- `get_odds` for real numbers to work with

+ 2. `puckapi-tool` -- `get_odds` for real numbers to work with

### "Should I bet this game?" / "Where's the edge?" / "Expected value"

1. `edge-detection` -- EV calculation, Kelly sizing, CLV

2. `odds-explorer` -- current market odds

3. `probability-calibration` -- verify model probabilities first

4. Requires: user must have a calibrated model

### "Backtest my model" / "Historical performance" / "Is my edge real?"

1. `backtesting` -- walk-forward backtest, strategy simulation

- 2. `sportsdatahq-tool` -- historical odds (heavy credits)

+ 2. `puckapi-tool` -- historical odds (heavy credits)

3. If model health check: backtesting includes model audit

### "Build an xG model" / "Expected goals from scratch" / "Shot quality model"

1. `xg-model-building` -- full xG pipeline from play-by-play

2. If user needs basics first: `hockey-analytics` for xG concept

### "Over/under prediction" / "Totals model" / "Will this game go over?"

1. `totals-modeling` -- pace, goalie matchup quality, under bias

- 2. `sportsdatahq-tool` -- `get_odds` for totals lines

+ 2. `puckapi-tool` -- `get_odds` for totals lines

### "Player props" / "Will McDavid score?" / "SOG prop" / "DFS"

1. `prop-modeling` -- TOI projection, per-60 rates, matchup adjustment

2. `player-scouting` -- player data

- 3. `sportsdatahq-tool` -- `get_player_stats`

+ 3. `puckapi-tool` -- `get_player_stats`

### "Build WAR" / "Player value" / "Contract analysis" / "RAPM"

1. `war-gar-decomposition` -- RAPM ridge regression, component GAR

2. `player-scouting` -- player data for context

- ### "EPA analysis" / "NFL play-by-play" / "QB evaluation"

- 1. `epa-situational-query` -- nflfastR queries, situational filters

- 2. Data source: `nfl_data_py` (free, external Python package), NOT Sports Data HQ. NFL data comes from free public sources, not SDH.

- ### "Should they go for it?" / "Fourth down" / "Was that the right call?"

- 1. `fourth-down-decision` -- EV framework, conversion tables

- 2. `epa-situational-query` -- if deeper NFL PBP analysis needed

### "Playoff odds" / "Will they make the playoffs?" / "Season simulation"

1. `playoff-simulation` -- Monte Carlo, bracket simulation

2. `elo-engineering` -- if rating system needed as input

- 3. `sportsdatahq-tool` -- remaining schedule

+ 3. `puckapi-tool` -- remaining schedule

### "Preview tonight's game" / "Sabres vs Leafs preview"

1. `game-preview` -- compound skill, loads data internally

- 2. `sportsdatahq-tool` -- multiple endpoints (~34 credits)

+ 2. `puckapi-tool` -- multiple endpoints (~34 credits)

### "Tonight's card" / "Full slate" / "All games tonight"

1. `daily-card` -- slate analysis, edge rankings

2. Requires: user's model for edge calculations

3. Heavy credits: ~10 credits per game on slate

### "Track my bets" / "Am I profitable?" / "CLV" / "Log this bet"

1. `bet-tracker` -- prediction logging, CLV, significance

2. If performance declining: route to `backtesting` for audit

### "Make a chart" / "Visualize" / "Calibration plot" / "Player card"

1. `visualization` -- chart type selection, code generation

2. Requires output from another skill (calibration, backtest, preview, etc.)

---

## When to Load Docs

- Unknown hockey term -> `docs/hockey-glossary.md`

- Unknown betting term -> `docs/betting-glossary.md`

- Need to pick a data tool -> `docs/tool-routing.md`

- Date/season confusion -> `docs/season-logic.md`

## When NOT to Use This Guide

Single-skill requests don't need dispatch. If someone says "devig these odds: +150 / -180" -> just load `odds-analysis`.