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 interface-qualitygit 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/interface-quality)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/interface-quality"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/interface-quality/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/interface-quality"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/interface-quality.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 | $0.00049 | $0.00762 |
| Opus 5.5 | $0.00020 | $0.00305 |
| Sonnet 5.5 | $0.00010 | $0.00152 |
| Haiku 4.5 | $0.00005 | $0.00076 |
Grade A, and why
interface-quality 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess interface quality in context
Assess whether the interface helps its intended users complete the task with clear hierarchy, dependable interaction and a coherent visual character. Preserve accepted product choices, including deliberate density and unusual styling. Distinguish an evidenced usability/accessibility problem from an aesthetic preference.
Use directly for a requested critique or as support during substantial design and authorized repair. Review remains read-only; fixes and shared-design annotations follow the requested scope. For a new direction, use visual design; for behavior use interaction design.
Establish the intended experience
Read the brief, references, accepted decisions and existing components. Identify the audience, primary task, content, platform and affected scope. Compare plausible visual directions where the choice is still open; connect the recommendation to those constraints. Reuse an accepted direction for ordinary changes.
Inspect and substantiate
Inspect rendered surfaces with realistic content and meaningful states, including relevant narrow layouts, failure/recovery and editing.
- Trace issues to source, tokens or component definitions where available.
- Follow the primary task and notice where the interface directs attention. Check whether the most prominent information and actions are the ones the task needs, and whether grouping and spacing explain which content belongs together.
- Examine typography at the sizes and lengths actually used, including dense data, labels and long values. Check whether semantic color, icons and motion communicate a consistent meaning and remain understandable without relying on one visual cue alone.
- Check content growth, zoom and locale/direction where they affect the task.
Verify applicable accessibility requirements and exercise keyboard/focus, labels, overlay behavior and reduced motion when runtime access permits. Separate static observations, runtime results, hypotheses and unavailable evidence. A finding must establish the user impact it claims; use an unverified label for a path that has not been exercised.
What ships with it
2 files 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 · +12 lines 42e8ffbfd814
- 2d ago Changed 092238ff8ff6
- 3d ago Changed 914cdc582598
- 5d ago First seen · 36 lines · 49 tokens per session scan A 21c24ac000af
interface-quality is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 762 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 2026-10-17.
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