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.
npx agentmods add instructions/rbraga01/builder-ai/claude-mdgit clone --depth 1 https://github.com/RBraga01/builder-aiWrote 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/rbraga01/builder-ai/claude-md)<a href="https://agentmods.dev/instructions/rbraga01/builder-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/rbraga01/builder-ai/claude-md.svg" alt="Measured on agentmods" 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 | $0.00600 | $0.00600 |
| Opus 5 | $0.00300 | $0.00300 |
| Sonnet 5 | $0.00120 | $0.00120 |
| Haiku 4.5 | $0.00060 | $0.00060 |
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 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.
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 resultsprompt-versioning— all prompts must be versioned inprompts/fallback-required— every LLM call must have a fallback path
Workflow Skills
rag-pipeline-design— chunking, embedding, retrieval, reranking, generationmodel-benchmarking— structured benchmarking before committing to a modelcontext-optimization— reduce cost and latency without quality lossai-cost-audit— audit and project LLM API spendai-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
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.
- 5d ago First seen · 63 lines · 600 tokens per session scan A a88a6166530b
builder-ai CLAUDE.md is an instructions file published in the GitHub repository RBraga01/builder-ai (2 stars, last pushed 1mo ago), licensed MIT. It adds 600 tokens to every session, about $0.0030 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.
Other instructions, from other repositories
avoid-ai-writing CLAUDE.md
Claude Code instructions for conorbronsdon/avoid-ai-writing, covering claude.md, what this is, repository structure, how to make changes and architecture of the skill.
Doberman-Core AGENTS.md
AGENTS.md instructions for DobermanCore/Doberman-Core, covering claude.md — doberman operating manual, 0. on startup (every session), 1. what this repository is, 2. architecture & extension points and 3. prime directives (non-negotiable).
Eval CLAUDE.md
Instructions for ai-twinkle/Eval, covering twinkle eval — 專案規範手冊（claude.md）, 目錄, 1. 專案定位與設計理念, 1.1 誕生背景 and 1.2 核心設計哲學.
TLDR CLAUDE.md
Instructions for 0p9b/TLDR, covering claude.md — tldr maintainer guide, product, source layout, edit rules and install paths.
TLDR AGENTS.md
Instructions for 0p9b/TLDR: @./skills/tldr/SKILL.md @./skills/tldr-commit/SKILL.md @./skills/tldr-review/SKILL.md @./skills/tldr-compress/SKILL.md.
Library-First-Engineering copilot-instructions.md
Instructions for StChiotis/Library-First-Engineering: You are an AI agent operating in a Library-First Engineering (LFE) repository. This adapter is a pointer. Canonical rules live in human-readable docs.