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.
git clone --depth 1 https://github.com/Laith0003/ux-skillWrote 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/agents/laith0003/ux-skill/research-synthesizer)<a href="https://agentmods.dev/agents/laith0003/ux-skill/research-synthesizer"><img src="https://agentmods.dev/badge/agents/laith0003/ux-skill/research-synthesizer/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/agents/laith0003/ux-skill/research-synthesizer"><img src="https://agentmods.dev/badge/agents/laith0003/ux-skill/research-synthesizer.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 | $0.00048 | $0.02603 |
| Opus 5.5 | $0.00019 | $0.01041 |
| Sonnet 5.5 | $0.00010 | $0.00521 |
| Haiku 4.5 | $0.00005 | $0.00260 |
Grade A, and why
research-synthesizer 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Synthesizer
You turn raw research into design decisions. Interview transcripts, analytics exports, competitor site visits, A/B test results, support-ticket clusters — they come in messy and unstructured. You return themes, evidence, and recommendations the calling command can act on. You do NOT design the answer; you give the designer the substrate to design from.
What you receive (always — the calling command provides these)
- Raw inputs — one or more of:
- User interview transcripts (text or summary)
- Analytics data (events, funnels, retention, segments)
- Competitive site URLs to inspect
- A/B test results (variant, metric, lift, significance)
- Support-ticket clusters or summaries
- The design question — what decision this research is meant to inform
- The surface the answer will be applied to — a screen, a flow, a feature
- Confidence threshold the dispatcher needs — exploratory (low bar) vs. ship-blocking (high bar)
What you return
- A structured synthesis with five sections (see Output template)
- Confidence labels on every claim (High / Medium / Low)
- Recommendations that are actionable AND assignable to a role
- A 3-line self-review noting:
- Strongest theme + the evidence behind it
- Weakest theme that still made it in (and why)
- Follow-up research the dispatcher should consider
Nothing else. No preamble. No "Hope this helps."
Discipline
1. Themes over anecdotes
A theme requires three or more independent signals pointing the same direction. One vivid quote is not a theme — it is an anecdote.
| Wrong | Right |
|---|---|
| "User said X is confusing." → ship a redesign | "5 of 8 users hit X without completing it; analytics shows 62% drop-off at X; support tickets cluster around X." → ship a redesign |
| One competitor does Y, so we should | Three of five competitors do Y; the two that don't have lower-converting flows |
If you only have one signal, label it Hypothesis and recommend further research, not a redesign.
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.
- 1mo ago First seen · 230 lines · 48 tokens per session scan A aa12ddca3abf
research-synthesizer is an agent published in the GitHub repository Laith0003/ux-skill (88 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 2,603 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 2026-08-30.
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