builder-ai: Instructions file for Codex

AGENTS.md

builder-ai AGENTS.md is an instructions file for Codex, OpenCode from RBraga01/builder-ai. It costs 483 tokens per session, scanned A, original, MIT.

A project instruction file that defines a roster of agents and skills for building language-model features.

In plain words
What is it for?
It helps enforce evaluation before shipping, prompt version control, fallback paths, retrieval-augmented generation design, model comparison, context reduction, cost audits, and safety reviews.
Why use it?
It gives the development team required checks and named workflows for prompts, models, costs, retrieval, and safety.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is RBraga01/builder-ai's own configuration. It tells Codex and OpenCode 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/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/RBraga01/builder-ai

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Per session 483 This file is loaded in full into every session.
When invoked 483 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 $0.00483 $0.00483
Opus 5.5 $0.00193 $0.00193
Sonnet 5.5 $0.00097 $0.00097
Haiku 4.5 $0.00048 $0.00048

Measured 1mo ago against content hash f2eb9044ad14, 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 AGENTS.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.

AGENTS.md · 34 lines

What it actually says

builder-ai — Agent & Skill Roster v1.0.0

Hard Gate Skills

Skill Description Triggers
eval-before-ship Blocks LLM features without documented eval results Before any PR that adds or modifies a prompt or model
prompt-versioning Enforces prompt version control in prompts/ Whenever writing or modifying a prompt
fallback-required Blocks LLM calls without defined fallback paths Before any PR that adds an LLM API call

Workflow Skills

Skill Description Triggers
rag-pipeline-design RAG pipeline design: chunking, embedding, retrieval, reranking, generation Designing or auditing a RAG feature
model-benchmarking Structured model comparison with cost-quality analysis Selecting a model for any feature
context-optimization Context reduction: prompt trimming, chunk reduction, caching Latency or cost issues, or approaching context limits
ai-cost-audit LLM spend audit and projection Pre-launch cost estimate or unexpected cost growth
ai-safety-review Safety review: injection, hallucination, abuse, agentic scope Before any user-facing LLM feature ships

Agents

Agent Tier Model Trigger
prompt-engineer Tier 2 claude-sonnet-4-6 Writing, iterating, or debugging prompts
eval-designer Tier 2 claude-sonnet-4-6 Designing eval suites, writing harness code
rag-architect Tier 1 claude-opus-4-8 Designing or debugging retrieval pipelines
model-selector Tier 2 claude-sonnet-4-6 Model comparison and selection
ai-safety-reviewer Tier 1 claude-opus-4-8 Safety review before user-facing features ship

Integration with A Team

If A Team is installed, builder-ai agents and skills slot in alongside the existing roster. No conflicts — all names are unique. builder-ai agents can be dispatched by the A Team orchestrator like any other specialist.

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 · 34 lines · 483 tokens per session scan A f2eb9044ad14

Subscribe to this mod's changes

builder-ai AGENTS.md is an instructions file published in the GitHub repository RBraga01/builder-ai (2 stars, last pushed 4d ago), licensed MIT. It adds 483 tokens to every session, about $0.0019 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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