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 skills add RBraga01/builder-design --skill ai-states-requiredgit 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/skills/rbraga01/builder-design/ai-states-required)<a href="https://agentmods.dev/skills/rbraga01/builder-design/ai-states-required"><img src="https://agentmods.dev/badge/skills/rbraga01/builder-design/ai-states-required/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/skills/rbraga01/builder-design/ai-states-required"><img src="https://agentmods.dev/badge/skills/rbraga01/builder-design/ai-states-required.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 | $0.00042 | $0.01434 |
| Opus 5 | $0.00021 | $0.00717 |
| Sonnet 5 | $0.00008 | $0.00287 |
| Haiku 4.5 | $0.00004 | $0.00143 |
Grade A, and why
ai-states-required 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 10d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI States Required
The Law
AN AI FEATURE WITHOUT DESIGNED STATES IS HALF A FEATURE.
"We'll add error states later" means users see broken UI in production.
"The happy path looks great" is not a UI design — it is a demo.
All 7 states designed, documented, and approved IS a complete AI feature design.
The 7 Required States
Every AI feature touchpoint must have a designed state for each:
| State | When It Appears | What Users Need |
|---|---|---|
| Loading | Request sent, waiting for first token | Progress signal, estimated wait, cancel option |
| Streaming | Tokens arriving, response building | Readable partial content, clear "generating" signal |
| Success | Generation complete, full response available | Result, confidence signal, actions (copy, retry, share) |
| Error | API failure, timeout, server error | Human error message, recovery action, no raw stack trace |
| Partial | Model answered but incompletely | Clear indication of incompleteness, option to continue |
| Uncertain | Low confidence, hedged response | Uncertainty signal, source citation, human review option |
| Empty | No input yet / no history / first run | Guidance, examples, prompt suggestions — not a blank void |
When to Use
Trigger before:
- Any PR that adds a new AI-powered UI feature
- Any PR that adds a new model call with user-visible output
- Designing a new agent interface or chat UI
- Adding AI capabilities to an existing feature
When NOT to Use
- Background AI jobs with no user-facing output (batch processing, background classification)
- Developer-only tooling where no end user sees the output
The Process
Step 1 — List Every AI Touchpoint
Map every place the user will see model output in this feature:
- Main response area
- Any inline predictions (autocomplete, suggestions)
- Status indicators (sidebar, header badges)
- Any secondary outputs (citations, related items, follow-up questions)
Each touchpoint needs its own 7-state design.
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.
- 10d ago First seen · 135 lines · 42 tokens per session scan A fe4ae939ba8d
ai-states-required is a skill published in the GitHub repository RBraga01/builder-design (2 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 1,434 once invoked, about $0.0002 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.
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