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.
curl -O https://raw.githubusercontent.com/ricardoherediaj/football-rag-intelligence/main/CLAUDE.mdgit clone --depth 1 https://github.com/ricardoherediaj/football-rag-intelligenceWrote 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.
[](https://agentmods.dev/instructions/ricardoherediaj/football-rag-intelligence/claude-md)<a href="https://agentmods.dev/instructions/ricardoherediaj/football-rag-intelligence/claude-md"><img src="https://agentmods.dev/badge/instructions/ricardoherediaj/football-rag-intelligence/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/ricardoherediaj/football-rag-intelligence/claude-md"><img src="https://agentmods.dev/badge/instructions/ricardoherediaj/football-rag-intelligence/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01673 | $0.01673 |
| Opus 5 | $0.00837 | $0.00837 |
| Sonnet 5 | $0.00335 | $0.00335 |
| Haiku 4.5 | $0.00167 | $0.00167 |
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 12d 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 — 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+/clearearly - 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:
- "Where does this belong?" — Derived data from Bronze → Dagster asset. Static reference → dbt seed. One-time → script is OK.
- "Does this scale to Championship, Jupiler Pro, Brasileirão?" — Parameterize by league/season from the start.
- "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.
- "Is there a built-in?" — dbt macro vs custom Python.
- "Can I delete 50% of this?"
- "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.
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.
- 12d ago First seen · 182 lines · 1,673 tokens per session scan A c7902fbc6fcd
football-rag-intelligence CLAUDE.md is an instructions file published in the GitHub repository ricardoherediaj/football-rag-intelligence (50 stars, last pushed 6mo ago), licensed MIT. It adds 1,673 tokens to every session, about $0.0084 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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