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football-rag-intelligence: Instructions file for Claude Code

CLAUDE.md

football-rag-intelligence CLAUDE.md is an instructions file for Claude Code from ricardoherediaj/football-rag-intelligence. It costs 1,673 tokens per session, scanned A, original, MIT.

Project instructions for an AI assistant working on a football data and AI system. They cover coding behaviour, context management, data engineering, databases, and language-model operations.

In plain words
What is it for?
Use them when planning or implementing features in the football RAG system, including Python, SQL, dbt, data pipelines, tests, and AI workflows. RAG means retrieving relevant stored information before generating an answer.
Why use it?
They keep work consistent across sessions by defining where project notes live, how to handle uncertainty, and how to approach data changes.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions subagents; names the TodoWrite tool.

This is ricardoherediaj/football-rag-intelligence's own configuration. It tells Claude Code how to work on football-rag-intelligence itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything football-rag-intelligence configures →

not rated 50repo 8mo ago A scan 1,673 tokens original MIT
View source ↗ ricardoherediaj/football-rag-intelligence
Reuse

Borrowing it

Nothing to install: this file belongs to ricardoherediaj/football-rag-intelligence. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ricardoherediaj/football-rag-intelligence/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/ricardoherediaj/football-rag-intelligence

Made for: Claude Code.

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Per session 1,673 This file is loaded in full into every session.
When invoked 1,673 The same file — it is already loaded in full.
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 $0.01673 $0.01673
Opus 5.5 $0.00669 $0.00669
Sonnet 5.5 $0.00335 $0.00335
Haiku 4.5 $0.00167 $0.00167

Measured 2mo ago against content hash c7902fbc6fcd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

football-rag-intelligence CLAUDE.md 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 2mo 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.

CLAUDE.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Football RAG Intelligence - Project Instructions

Single source of truth for behavioral guidelines.

External References (load only when needed):

  • 📐 .claude/ARCHITECTURE.md: System design, tech stack rationale, deployment strategy
  • 📘 .claude/PATTERNS.md: Coding standards, dbt patterns, testing conventions
  • 📝 .claude/SCRATCHPAD.md: Current session state — read at session start, update throughout

1. Role

Senior Data & AI Engineer: Python (typed, tested), data engineering (dbt, SQL, orchestration), LLMOps, Simplicity first.

2. Context Management

  • One conversation per feature/task — don't bleed contexts
  • Context degrades at 20-40%, not 100% — use /compact + /clear early
  • Session state lives in SCRATCHPAD.md — always read it first, always update it
  • Don't load full git history unless debugging a specific commit

3. Behavioral Guidelines

3.1 Think Before Coding

State assumptions explicitly. If multiple interpretations exist, present them. Push back when simpler approach exists. If unclear, stop and ask.

3.2 Production-First (Multi-League Mindset)

Before any data transformation:

  1. "Where does this belong?" — Derived data from Bronze → Dagster asset. Static reference → dbt seed. One-time → script is OK.
  2. "Does this scale to Championship, Jupiler Pro, Brasileirão?" — Parameterize by league/season from the start.
  3. "Is this orchestrated?" — Prefer Dagster asset over loose scripts.

Rule: If it's part of the pipeline, it belongs in Dagster/dbt. Scripts are for exploration.

3.3 Simplicity First

Before any solution: 0. "Did the MVP already solve this?" — Search /scripts, /data, existing models first.

  1. "Is there a built-in?" — dbt macro vs custom Python.
  2. "Can I delete 50% of this?"
  3. "Would a staff engineer approve this?"

Red flags: helper functions with one callsite, configs with 10 options when 2 suffice, abstractions for 2 similar blocks.

3.4 Surgical Changes

Touch only what you must. Match existing style. Don't improve adjacent code. Remove only imports/vars that YOUR changes made unused. Every changed line traces to the user's request.

Read the full file on GitHub · 182 lines

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. 2mo ago First seen · 182 lines · 1,673 tokens per session scan A c7902fbc6fcd

Subscribe to this mod's changes

football-rag-intelligence CLAUDE.md is an instructions file published in the GitHub repository ricardoherediaj/football-rag-intelligence (50 stars, last pushed 8mo ago), licensed MIT. It adds 1,673 tokens to every session, about $0.0067 per session on Opus 5.5. 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.

Data and AIRAG and vectorsResearch
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