User Research Analysis
CheckedAnalyzes user research data (interviews, surveys, usability tests) to identify key themes and actionable insights.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add aj-geddes/useful-ai-prompts --skill user-research-analysis -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
aj-geddes
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 3f5182cfd7
- Scanned
- 7 files, 329 lines
About this skill
user-research-analysis
What it does
This skill enables AI agents to systematically gather, organize, and synthesize information from diverse sources to support informed decision-making. It transforms raw data into structured insights, allowing agents to act as virtual researchers for complex queries.
When to use it
- Conducting market analysis by aggregating competitor pricing and feature sets from public web pages.
- Summarizing long-form academic papers or industry reports into key takeaways for a team meeting.
- Investigating user feedback trends across multiple support tickets or social media platforms.
- Preparing briefing materials by extracting specific facts about historical events or technical specifications.
Key capabilities
- Information Retrieval: Accesses and parses content from various digital sources to find relevant data points.
- Data Synthesis: Combines disparate pieces of information into a coherent narrative or structured summary.
- Contextual Analysis: Identifies patterns, trends, and significant details within large volumes of text.
Example prompts
- "Research the top five features of competing CRM software released in the last quarter and summarize their pros and cons."
- "Gather recent news articles about supply chain disruptions in the automotive industry and highlight the most common causes mentioned."
- "Analyze the feedback on our latest product update from the community forum and categorize the top three user complaints."
Tips & gotchas
Ensure you provide clear constraints on the scope of research (e.g., specific timeframes or domains) to prevent the agent from retrieving irrelevant or outdated information. This skill relies on the availability of public data; it cannot access private databases or proprietary internal documents without explicit permissions.