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 nexus-labs-automation/mobile-observability --skill interaction-latencygit clone --depth 1 https://github.com/nexus-labs-automation/mobile-observabilityWrote 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/nexus-labs-automation/mobile-observability/interaction-latency)<a href="https://agentmods.dev/skills/nexus-labs-automation/mobile-observability/interaction-latency"><img src="https://agentmods.dev/badge/skills/nexus-labs-automation/mobile-observability/interaction-latency/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/nexus-labs-automation/mobile-observability/interaction-latency"><img src="https://agentmods.dev/badge/skills/nexus-labs-automation/mobile-observability/interaction-latency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00035 | $0.00341 |
| Opus 5 | $0.00017 | $0.00170 |
| Sonnet 5 | $0.00007 | $0.00068 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
interaction-latency 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.
What it actually says
Interaction Latency
Time from user tap to action successfully completed.
When to Use
- "Add to cart" button tapped → cart updated
- "Submit" button tapped → form processed
- "Like" button tapped → state changed
- Any tap that triggers async work
Measurement Pattern
TAP → START_SPAN → [async work] → END_SPAN
- Capture tap timestamp
- Start span with operation name
- End span when action confirms success
- Include success/failure outcome
Key Thresholds
| Rating | Duration |
|---|---|
| Good | <300ms |
| Acceptable | <1s |
| Poor | >1s |
Implementation
See references/ui-performance.md (Entry Point Latency section) for platform-specific code.
Common Mistakes
- Ending span on API call start (not completion)
- Not tracking failure cases
- Missing the tap timestamp (starting late)
Related Skills
- See
skills/navigation-latencyfor screen-to-screen transitions (vs single-tap actions) - Combine with
skills/user-journey-trackingfor friction detection on key interactions
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 · 58 lines · 35 tokens per session scan A c42cb2b8c42e
interaction-latency is a skill published in the GitHub repository nexus-labs-automation/mobile-observability (116 stars, last pushed 17d ago), licensed MIT. It adds 35 tokens to every session and 341 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 2026-08-30.
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