builder-ai: Instructions file for Claude Code

CLAUDE.md

builder-ai CLAUDE.md is an instructions file for Claude Code from RBraga01/builder-ai. It costs 600 tokens per session, scanned A, original, MIT.

Repository instructions for builder-ai, a pack of skills and agents for building products that use large language models. It covers prompt writing, testing, information retrieval, model comparison, cost, and safety.

In plain words
What is it for?
Use them when developing or reviewing LLM features, including retrieval pipelines, model benchmarks, prompt changes, cost reviews, and safety checks.
Why use it?
They set required checks before shipping, such as testing LLM features, versioning prompts, and defining a fallback when a model call fails.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: reads .claude/ paths.

This is RBraga01/builder-ai's own configuration. It tells Claude Code how to work on builder-ai 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 builder-ai configures →

Reuse

Borrowing it

Nothing to install: this file belongs to RBraga01/builder-ai. 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/RBraga01/builder-ai/master/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/RBraga01/builder-ai

Made for: Claude Code.

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Per session 600 This file is loaded in full into every session.
When invoked 600 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 $0.00600 $0.00600
Opus 5.5 $0.00240 $0.00240
Sonnet 5.5 $0.00120 $0.00120
Haiku 4.5 $0.00060 $0.00060

Measured 1mo ago against content hash a88a6166530b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

builder-ai 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 1mo 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 · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

builder-ai — Build LLM Products That Don't Fail Silently v1.0.0

A drop-in skill and agent pack for teams building LLM-powered products. Three hard gates block incomplete work. Five workflow skills cover the full build cycle. Five specialist agents handle prompt engineering, evaluation, RAG, model selection, and safety.

Works standalone. Works alongside A Team.

Skills in This Pack

Hard Gates (mandatory before shipping)

  • eval-before-ship — no LLM feature ships without documented eval results
  • prompt-versioning — all prompts must be versioned in prompts/
  • fallback-required — every LLM call must have a fallback path

Workflow Skills

  • rag-pipeline-design — chunking, embedding, retrieval, reranking, generation
  • model-benchmarking — structured benchmarking before committing to a model
  • context-optimization — reduce cost and latency without quality loss
  • ai-cost-audit — audit and project LLM API spend
  • ai-safety-review — injection, hallucination, abuse, and agentic scope review

Agents in This Pack

Agent Trigger
prompt-engineer Writing, iterating, or debugging prompts
eval-designer Designing evaluation suites for LLM outputs
rag-architect Designing or debugging retrieval pipelines
model-selector Selecting the cost-optimal model for a task
ai-safety-reviewer Safety and abuse review before user-facing features ship

Expected Directory Layout After Installation

your-project/
├── prompts/              ← versioned prompts (created by prompt-engineer)
│   └── feature-name/
│       ├── v1.0.0.md
│       └── CHANGELOG.md
├── evals/                ← eval suites and results (created by eval-designer)
│   └── feature-name/
│       ├── test-set.jsonl
│       └── results-<date>.md
├── benchmarks/           ← model comparison results (created by model-selector)
├── cost-audit/           ← cost audit reports (created by ai-cost-audit skill)
├── safety-reviews/       ← safety review documents (created by ai-safety-reviewer)
├── skills/               ← this pack's skills
└── .claude/agents/       ← this pack's agents

Read the full file on GitHub · 63 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. 1mo ago First seen · 63 lines · 600 tokens per session scan A a88a6166530b

Subscribe to this mod's changes

builder-ai CLAUDE.md is an instructions file published in the GitHub repository RBraga01/builder-ai (2 stars, last pushed 10d ago), licensed MIT. It adds 600 tokens to every session, about $0.0024 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 2026-08-31.

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