buzzr-sports-engine

buzzr-sports-engine is a skill for Codex from Buzzr-app/dfs-engine. It costs 110 tokens per session (1,278 once invoked), scanned A, original, MIT.

A sports-betting calculation and validation toolkit for odds, fantasy contests, betting history, and game-entertainment scores.

In plain words
What is it for?
Use it to calculate fair American-odds lines, parlay value, expected value, Kelly stakes, closing-line value, and to validate or grade DFS entries such as PrizePicks- or Underdog-style picks.
Why use it?
It provides repeatable calculations and rule-based checks for questions where an approximate answer could lead to a wrong bet settlement or bankroll decision.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to calculate fair American-odds lines, parlay value, expected value, Kelly stakes, closing-line value, and to validate or grade DFS entries such as PrizePicks- or Underdog-style picks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/buzzr-app/dfs-engine/buzzr-sports-engine
Install

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.

Any agent
npx skills add Buzzr-app/dfs-engine --skill buzzr-sports-engine
Clone the repo
git clone --depth 1 https://github.com/Buzzr-app/dfs-engine

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for buzzr-sports-engine

README.md
[![agentmods](https://agentmods.dev/badge/skills/buzzr-app/dfs-engine/buzzr-sports-engine.svg)](https://agentmods.dev/skills/buzzr-app/dfs-engine/buzzr-sports-engine)
Your own site
<a href="https://agentmods.dev/skills/buzzr-app/dfs-engine/buzzr-sports-engine"><img src="https://agentmods.dev/badge/skills/buzzr-app/dfs-engine/buzzr-sports-engine.svg" alt="Measured on agentmods" height="20"></a>
Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,278 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00110 $0.01278
Opus 5 $0.00055 $0.00639
Sonnet 5 $0.00022 $0.00256
Haiku 4.5 $0.00011 $0.00128

Measured 8d ago against content hash 95d1aa3b9d75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

buzzr-sports-engine 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 8d 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.

skills/buzzr-sports-engine/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Buzzr Sports Engine

Use Buzzr when the user needs auditable sports math instead of an estimated calculation. Prefer the MCP server for interactive analysis and the @buzzr/* packages for application code, custom policies, provider adapters, or high-volume pipelines.

Route the request

  1. Identify the domain:
    • DFS settlement: list_book_policies, validate_dfs_entry, grade_dfs_entry, or grade_dfs_entries.
    • Odds and bankroll math: fair_line, closing_line_value, parlay_value, or kelly_stake.
    • Historical analysis: summarize_bet_history.
    • Entertainment scoring: predict_game_buzz or rank_games.
  2. Use the MCP tools when they are available in the current session.
  3. If the tools are unavailable, help configure the local server or use the matching npm package in code. Do not imitate a tool result and present it as engine output.
  4. Read references/mcp-tools.md for the 11-tool catalog, limits, and response contracts.
  5. Before any operator-specific DFS conclusion, follow references/operator-safety.md.

Configure the local MCP server

For repeatable work, pin the reviewed published version:

[mcp_servers.buzzr]
command = "npx"
args = ["-y", "@buzzr/[email protected]"]

Use @buzzr/mcp@latest only when automatic upgrades are acceptable. The server uses stdio, writes protocol messages only to stdout, and needs no API key. Restart the client after changing its MCP configuration.

If startup fails, check these in order:

  1. Node.js is version 22 or newer.
  2. The package version exists: npm view @buzzr/[email protected] version.
  3. The executable starts cleanly: npx -y @buzzr/[email protected].
  4. The client launches the command directly rather than through an interactive shell.

Settle DFS entries

Call list_book_policies before grading. Use only a policy/play type reported as executable: true. A draft fixture is documentation, not a grading implementation.

Supply the slip's own bookId, playTypeId, displayedMultiplier, stake, placed timestamp, and leg details. Supply observed stats as actual or actualsByLegId; the MCP server does not fetch box scores. Mark DNP, void, or other operator rulings explicitly when known.

Read the full file on GitHub · 92 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 8d ago First seen · 92 lines · 110 tokens per session scan A 95d1aa3b9d75

Subscribe to this mod's changes

buzzr-sports-engine is a skill published in the GitHub repository Buzzr-app/dfs-engine (0 stars, last pushed 5d ago), licensed MIT. It adds 110 tokens to every session and 1,278 once invoked, about $0.0006 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 2026-08-31.