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 Dragoon0x/taste-skills --skill timing-feedbackgit clone --depth 1 https://github.com/Dragoon0x/taste-skillsWrote 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/dragoon0x/taste-skills/timing-feedback)<a href="https://agentmods.dev/skills/dragoon0x/taste-skills/timing-feedback"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/timing-feedback/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/dragoon0x/taste-skills/timing-feedback"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/timing-feedback.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 | $0.00044 | $0.00348 |
| Opus 5 | $0.00022 | $0.00174 |
| Sonnet 5 | $0.00009 | $0.00070 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
timing-feedback 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 9d 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
Timing & Feedback
Every user action deserves acknowledgment. The question is what kind and how fast.
How to use
/timing-feedbackApply timing and feedback constraints to interaction design in this conversation.
Constraints
Timing Scale
- Instant (< 100ms): Direct manipulation. Button presses, toggles, drags. Any delay here feels broken.
- Fast (100-300ms): Page changes, panel opens, filter applications. Most UI animation lives here.
- Deliberate (300ms-1s): Complex operations. Loading a view, running a search. User accepts the wait because the action feels significant.
- Patient (> 1s): Needs explicit feedback. Progress indicator, skeleton, status message. Silence here feels like failure.
Feedback Types
- Visual: Color change, animation, state shift. Minimum viable feedback.
- Spatial: Element movement, expansion, collapse. Communicates where something went.
- Informational: Text confirmation, count update, status change. Communicates what happened.
- MUST provide at least one feedback type for every user action
- SHOULD mute the device and verify: can you still tell what's happening?
Anti-Patterns
- Identical response timing for all actions regardless of significance
- No feedback for destructive actions (delete, remove, disconnect)
- Spinners where skeletons would preserve spatial context
- Feedback animations that outlast the actual operation
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.
- 9d ago First seen · 34 lines · 44 tokens per session scan A 3cc7760e6be9
timing-feedback is a skill published in the GitHub repository Dragoon0x/taste-skills (4 stars, last pushed 6mo ago), licensed MIT. It adds 44 tokens to every session and 348 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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