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/everything-design-taste --skill feedback-ratinggit clone --depth 1 https://github.com/Dragoon0x/everything-design-tasteWrote 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/everything-design-taste/feedback-rating)<a href="https://agentmods.dev/skills/dragoon0x/everything-design-taste/feedback-rating"><img src="https://agentmods.dev/badge/skills/dragoon0x/everything-design-taste/feedback-rating/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/everything-design-taste/feedback-rating"><img src="https://agentmods.dev/badge/skills/dragoon0x/everything-design-taste/feedback-rating.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 | $0.00020 | $0.00311 |
| Opus 5 | $0.00010 | $0.00156 |
| Sonnet 5 | $0.00004 | $0.00062 |
| Haiku 4.5 | $0.00002 | $0.00031 |
Grade A, and why
feedback-rating 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 6d 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
Feedback & Rating Patterns
In-App Feedback
- Timing: After a completed task, not during
- Format: Simple scale (1-5 or thumbs up/down) + optional text
- Frequency: Don't ask more than once per session / once per week
- Dismissable: Always allow skipping without penalty
NPS (Net Promoter Score)
- Single question: "How likely are you to recommend [product] to a colleague?"
- Scale: 0-10
- Follow-up: "What's the main reason for your score?" (open text)
- Don't ask on first visit or during onboarding
- Quarterly or after key milestones
Review Display
- Show average rating and total count
- Distribution bar chart (how many 5-star, 4-star, etc.)
- Most helpful reviews first, not most recent
- Filter by rating, sort by recency or helpfulness
- Show verified purchase/user badges
- Allow marking reviews as helpful
Feedback Forms
- Keep it short (3-5 questions max)
- Mix closed (scale, multiple choice) and open (text) questions
- Show progress if multi-step
- Thank the user meaningfully after submission
- Actually follow up on feedback (close the loop)
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.
- 6d ago First seen · 36 lines · 20 tokens per session scan A c61904e8b2d6
feedback-rating is a skill published in the GitHub repository Dragoon0x/everything-design-taste (11 stars, last pushed 5mo ago), licensed MIT. It adds 20 tokens to every session and 311 once invoked, about $0.0001 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 2026-09-03.
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