user-research-synthesis

user-research-synthesis is a skill for Claude Code from ramybarsoum/prodkit. It costs 19 tokens per session (453 once invoked), scanned A, original, MIT.

A process for turning user interview notes, transcripts, and observations into product insights and actions.

In plain words
What is it for?
Use it to synthesize interviews, identify relevant previous research and project context, and produce actionable product insights.
Why use it?
It helps make sense of qualitative research and connect findings with existing product principles, research, strategy, and project documents.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the prodkit plugin — 10 skills shipped together

Good fit Use it to synthesize interviews, identify relevant previous research and project context, and produce actionable product insights.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ramybarsoum/prodkit/user-research-synthesis
Install

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.

Any agent
npx skills add ramybarsoum/prodkit --skill user-research-synthesis
Clone the repo
git clone --depth 1 https://github.com/ramybarsoum/prodkit

Made for: Claude Code.

Or install prodkit, the plugin that ships this one along with the rest of its 10 skills.

Wrote 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.

agentmods badge for user-research-synthesis

README.md
[![agentmods](https://agentmods.dev/badge/skills/ramybarsoum/prodkit/user-research-synthesis.svg)](https://agentmods.dev/skills/ramybarsoum/prodkit/user-research-synthesis)
Your own site
<a href="https://agentmods.dev/skills/ramybarsoum/prodkit/user-research-synthesis"><img src="https://agentmods.dev/badge/skills/ramybarsoum/prodkit/user-research-synthesis.svg" alt="Measured on agentmods" height="20"></a>
Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 453 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00019 $0.00453
Opus 5 $0.00010 $0.00227
Sonnet 5 $0.00004 $0.00091
Haiku 4.5 $0.00002 $0.00045

Measured 7d ago against content hash 097557ac6741, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

user-research-synthesis 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 7d 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.

skills/user-research-synthesis/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interaction style: Use the AskUserQuestion tool for all structured questions in this skill. Group related questions together (2-3 per call) rather than asking one at a time.

/user-research-synthesis - Turn Interview Data Into Insights

When the PM types /user-research-synthesis, transform raw user interview notes, transcripts, and observations into actionable product insights.

Context Routing Logic (Internal - for Claude)

Automatic Context Checks: When this skill is invoked, immediately check:

Source Files/Folders Search Terms What to Extract
Product Principles knowledge/company/product-principles.md product principles, core values Which principles this feature embodies and how
Existing Research knowledge/research/*.md topic from chat, user segments Previous findings to avoid duplication
Related PRDs projects/*/ problem related to interviews Problem framing and hypothesis
Strategy Context knowledge/strategy/*.md user segment, strategic fit How findings ladder to strategy
Previous Synthesis work/research/ topic name Past research to build on
Interview Guides knowledge/research/interview-guides/ topic What questions were asked

Context Priority:

  1. Product principles alignment FIRST
  2. Raw interview data SECOND (always use verbatim quotes)
  3. Related PRDs and problem statements THIRD
  4. Previous research on related topics FOURTH
  5. Strategic context FIFTH

Cross-Skill Links:

  • After synthesis → Link to /prd-draft to turn insights into feature spec
  • If about competitor mentions → Link to /competitor-analysis
  • If about retention → Link to /retention-analysis for churn patterns
  • If informing strategy → Link to /write-prod-strategy

Read the full file on GitHub · 44 lines

Changes

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.

  1. 7d ago First seen · 44 lines · 19 tokens per session scan A 097557ac6741

Subscribe to this mod's changes

user-research-synthesis is a skill published in the GitHub repository ramybarsoum/prodkit (4 stars, last pushed 5mo ago), licensed MIT. It adds 19 tokens to every session and 453 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 2026-08-31.

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