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 w95/awesome-claude-corporate-skills --skill user-research-synthesizergit clone --depth 1 https://github.com/w95/awesome-claude-corporate-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/w95/awesome-claude-corporate-skills/user-research-synthesizer)<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/user-research-synthesizer"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/user-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/skills/w95/awesome-claude-corporate-skills/user-research-synthesizer"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/user-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 | $0.00040 | $0.04329 |
| Opus 5 | $0.00020 | $0.02165 |
| Sonnet 5 | $0.00008 | $0.00866 |
| Haiku 4.5 | $0.00004 | $0.00433 |
Grade A, and why
user-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 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.
How it starts
The opening of the file, as written. The whole thing — 571 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Research Synthesizer
Overview
The User Research Synthesizer skill enables product managers to extract meaningful insights from multiple research sources, identify patterns, and translate findings into actionable product recommendations. It bridges qualitative and quantitative research.
When to Use This Skill
- Consolidating findings from customer research
- Identifying user needs and pain points
- Mapping customer journey and touchpoints
- Discovering feature opportunities
- Validating product assumptions
- Creating evidence-based recommendations
- Communicating research insights to stakeholders
Research Synthesis Methodology
Multi-Source Research Consolidation
Research Sources Integration:
Qualitative Research (What users think and feel)
- Customer interviews (depth, stories, motivations)
- Usability testing (observed behavior, pain points)
- Focus groups (broader perspectives, discussion)
- Open-ended surveys (rich feedback, themes)
Quantitative Research (How many users experience something)
- Usage analytics (feature adoption, engagement patterns)
- Surveys (scale of opinions, segment differences)
- Customer feedback (NPS comments, satisfaction scores)
- A/B testing results (statistical validation)
Behavioral Signals (What users actually do)
- Product analytics (feature usage, drop-off points)
- Support tickets (problems experienced)
- Feature request trends (demand signals)
- Churn analysis (why users leave)
Synthesis Process Framework
Step 1: Data Collection
- Compile all research raw data
- Organize by source and date
- Ensure consistent note-taking format
- Document research context and sample size
Step 2: Individual Source Analysis
- Interview transcription and tagging
- Survey data cleaning and basic analysis
- Analytics report generation
- Support ticket categorization
Step 3: Cross-Source Pattern Identification
- Identify themes appearing in multiple sources
- Note conflicting findings (important!)
- Look for statistical validation of qualitative themes
- Assess confidence in findings
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 · 571 lines · 40 tokens per session scan A 456d60166f82
user-research-synthesizer is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (198 stars, last pushed 6mo ago), licensed MIT. It adds 40 tokens to every session and 4,329 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 2026-09-03.
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