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 joao-aires/agent-skills-public --skill interaction-designgit clone --depth 1 https://github.com/joao-aires/agent-skills-publicWrote 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/joao-aires/agent-skills-public/interaction-design)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/interaction-design"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/interaction-design/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/joao-aires/agent-skills-public/interaction-design"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/interaction-design.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 | $0.00056 | $0.01123 |
| Opus 5.5 | $0.00022 | $0.00449 |
| Sonnet 5.5 | $0.00011 | $0.00225 |
| Haiku 4.5 | $0.00006 | $0.00112 |
Grade A, and why
interaction-design 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 yesterday.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design interactions before implementation
Use this with visual design for product-derived visual direction, tokens and representative rendered review. This skill owns behavior and coverage; technical conventions own implementation for the selected stack. Use both disciplines for a new interface. Apply it automatically to relevant requested work; users do not need to remember the skill name. A typo, a tiny token adjustment or unchanged interaction needs proportionate reasoning, not a fresh full design document.
Discover the full affected experience
Read the request, accepted UX/product decisions, references and existing components/routes. Inspect the rendered application when available and distinguish observed behavior from code assumptions. Map user roles, tasks and entry/exit points before choosing widgets. Preserve established branding, density, navigation and business language unless changing them is the request.
For a cross-cutting change, trace shared primitives, caller overrides and alternate/conditional entry points. Keep a concise coverage record of the affected surfaces, meaningful states, intended shared behavior and verification status in existing notes. Derive its scope from the request and actual application, including relevant roles/platforms.
Specify the interaction before coding
For each reusable pattern, establish the relevant contract before implementation:
| Concern | Specify |
|---|---|
| Task and state | User goal, visible information hierarchy, primary/secondary actions, navigation/deep-link/back behavior, state ownership and success/failure transitions. |
| Failure and ongoing work | Loading, empty, validation, disabled/permission, error/retry, unsaved edits/cancel, duplicate submission and destructive/recovery behavior; async progress, stale responses and persistence/reload where needed. |
| Accessible interaction | Keyboard/focus, dialog open/close and focus return, labels, announcements and responsive changes. |
| Supported platforms | Touch/safe areas, Back/deep links, permission denial, offline/reconnection and foreground/background lifecycle. Preserve drafts across errors and lifecycle transitions; scope offline behavior to the accepted product. |
| Shared patterns | Page/drawer/dialog choice from task complexity and continuity, navigational submenus versus sibling tabs/context actions, shared behavior/tokens and justified contextual variants. |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday Changed · +11 lines f8a4d2eadaaf
- 2d ago Changed 6e212c522812
- 3d ago Changed · -4 lines 234958355cba
- 5d ago Changed · +2 lines e1ca02723335
- 7d ago First seen · 50 lines · 56 tokens per session scan A 28946957ca51
interaction-design is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 1,123 once invoked, about $0.0002 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 2026-10-15.
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