goldenmatch: Instructions file for Claude Code

CLAUDE.md

goldenmatch CLAUDE.md is an instructions file for Claude Code from benseverndev-oss/goldenmatch. It costs 5,169 tokens per session, scanned A, original, MIT.

Project instructions for Golden Suite, a multi-package code repository that contains Python, Rust, TypeScript, dbt, and Actions packages. They describe how to build, test, merge, and work across the repository.

In plain words
What is it for?
Working in the Golden Suite monorepo, running its checks, following CI and merge-queue rules, and resolving test or package issues.
Why use it?
They give coding agents the project context and rules needed to make consistent changes. They also explain how to handle flaky tests and package-specific guidance.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md.

This is benseverndev-oss/goldenmatch's own configuration. It tells Claude Code how to work on goldenmatch 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 goldenmatch configures →

Reuse

Borrowing it

Nothing to install: this file belongs to benseverndev-oss/goldenmatch. 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/benseverndev-oss/goldenmatch/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/benseverndev-oss/goldenmatch

Made for: Claude Code.

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Per session 5,169 This file is loaded in full into every session.
When invoked 5,169 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 $0.05169 $0.05169
Opus 5 $0.02584 $0.02584
Sonnet 5 $0.01034 $0.01034
Haiku 4.5 $0.00517 $0.00517

Measured 5d ago against content hash 556f47a8cc27, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

goldenmatch 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 5d 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 · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Golden Suite monorepo

Polyglot monorepo: packages/{python,rust,typescript,dbt,actions}. Per-package CLAUDE.md files own package-specific context.

STANDING RULE — flaky test first. The moment a test is observed flaky (intermittent CI red, a re-queue that goes green, a "passes locally / fails in CI" report), STOP the current work and fix the flakiness first, then resume. A flaky test is a real defect — it hides regressions and erodes the merge gate — so it takes priority over the feature in flight, not a "later" backlog item. Fix the ROOT cause (determinism, isolation, resource hardening), not the symptom (no blind retries/rerun bandaids, no loosened assertions); the swallowed-error / non-WAL-SQLite / xdist-shared-state classes are the usual suspects.

North Star (the pull that colors every decision): be the tool any developer reaches for by default for entity resolution. It is never "done" — defaults are re-earned every release. The full statement + the five decision-test commitments (zero-config, scale-invariant correctness, shared-capabilities-conform, approach-the-expert, never-black-box) live in context-network/foundation/project-definition.md. When two changes compete, take the one that advances it.

Architecture governing frame (colors every architectural decision, the way the North Star colors product decisions): GoldenMatch is one product, two engines, many surfaces — an Arrow-native, Rust-authoritative Identity Compute Engine + a transaction-native Identity Control Plane (SQLite/Postgres), exposed through many surfaces governed by spec + conformance. The full frame + roadmap live in context-network/architecture/one-product-two-engines.md (decision context-network/decisions/0047-one-product-two-engines-architecture.md). Read it before any architectural change; the change must conform or amend the frame (doc + 0047) in the same PR. Decision tests every change must pass:

  • One authoritative semantic owner per capability — Rust where a clean shared core exists; pure-Python / standalone-TS algorithms are classified, conformance-tested fallbacks, not co-equal sources of truth. Am I adding a second source of truth for behavior that already has an owner?
  • Arrow at bulk boundaries, not the universal calling convention — smallest stable primitive for scalar/small calls. Am I paying Arrow/FFI marshaling on a small call where two strings or a list[str] is cleaner?
  • Compute vs. control stay distinct — the compute engine is Arrow/batch; the control plane is a transaction-native state machine (stable IDs, merge/split, provenance, audit). Am I forcing stateful identity logic into a columnar kernel, or vice versa?
  • Kernelize on measurement — measure the whole path (conversion + orchestration), not a Rust-loop-vs-Python-loop microbench; state the motivation class (perf / semantic single-sourcing / portability / safety / maintainability).
  • Conformance defines correctness — a new backend/binding/fallback proves itself against the conformance suite (exact / numerically-equivalent / semantically-equivalent / intentionally-divergent), not by calling the same library. DataFusion/Ray/Sail/Ballista/Spark are replaceable backends, none synonymous with GoldenMatch.

Read the full file on GitHub · 133 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. 5d ago Changed · +1 lines · +90 tokens per session 556f47a8cc27
  2. 9d ago First seen · 132 lines · 5,079 tokens per session scan A 1824466c2f85

Subscribe to this mod's changes

goldenmatch CLAUDE.md is an instructions file published in the GitHub repository benseverndev-oss/goldenmatch (131 stars, last pushed today), licensed MIT. It adds 5,169 tokens to every session, about $0.0258 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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