Borrowing it
Nothing to install: this file belongs to RBraga01/builder-design. 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/RBraga01/builder-design/master/AGENTS.mdgit clone --depth 1 https://github.com/RBraga01/builder-designWrote 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-design/agents-md)<a href="https://agentmods.dev/instructions/rbraga01/builder-design/agents-md"><img src="https://agentmods.dev/badge/instructions/rbraga01/builder-design/agents-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/rbraga01/builder-design/agents-md"><img src="https://agentmods.dev/badge/instructions/rbraga01/builder-design/agents-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 | $0.00547 | $0.00547 |
| Opus 5.5 | $0.00219 | $0.00219 |
| Sonnet 5.5 | $0.00109 | $0.00109 |
| Haiku 4.5 | $0.00055 | $0.00055 |
Grade A, and why
builder-design 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.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agents — builder-design v1.0.0
5 agents for AI UI design, critique, and accessibility review.
ai-ui-designer (Opus)
Purpose: Full AI component design — from spec to token-compliant implementation.
Use when: Starting a new AI feature UI from scratch, or when a component needs to be rebuilt to meet the AI-native pattern requirements.
Produces:
design/specs/<feature>.md— layout, states, copy, interactionsdesign/ai-states/<feature>.md— all 7 states- Token-compliant component implementation
Does not: Write component code without a spec. Hardcode any values.
ux-critic (Sonnet)
Purpose: Structured critique of AI feature UI against all 5 skill areas.
Use when: Any AI feature UI is drafted and before it ships.
Output: design/reviews/<feature>/<date>-ux-critique.md
Verdict format: STATES / SPEC / COMPONENTS / PROMPT UX / TOKEN COMPLIANCE — each PASS / WARN / BLOCK. Overall: PASS / CONDITIONAL / BLOCK.
Does not: Produce suggestions. Issues are BLOCK, WARN, or NOTE.
state-designer (Sonnet)
Purpose: Maps all 7 required states before component code is written.
Use when: Starting any new AI feature — before any component is designed.
Produces: design/ai-states/<feature>.md with all 7 states + 3 edge cases.
Does not: Move to component design until all 7 states are defined.
prompt-ux-designer (Sonnet)
Purpose: Designs the prompt input experience — pattern, suggestions, feedback loop, constraints.
Use when: Designing any AI prompt input or chat interface.
Produces: design/specs/<feature>-prompt-ux.md with input pattern, suggestion system, 6-state feedback loop, and constraint definitions.
Does not: Leave suggestion copy as "TBD." Uses Enter-to-send for multi-line input. Ships without a [Stop] action.
accessibility-reviewer (Sonnet)
Purpose: Accessibility audit for AI feature UIs — ARIA, keyboard, contrast, cognitive load.
Use when: Before any AI feature UI ships.
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.
- 1mo ago First seen · 69 lines · 547 tokens per session scan A 1f347bba8021
builder-design AGENTS.md is an instructions file published in the GitHub repository RBraga01/builder-design (2 stars, last pushed 8d ago), licensed MIT. It adds 547 tokens to every session, about $0.0022 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.
Other instructions, from other repositories
ai-agent-rules-generator ui-design.instructions.md
Glitch Payment Gateway admin UI design rules — mandatory element & component reference for WooCommerce settings.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.