Customer Research
Nexus-JPF/note-companion
When the user wants to conduct, analyze, or synthesize customer research.
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights.
Install Sentiment Analysis
$ npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install majiayu000/claude-skill-registry sentiment-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/sentiment-analysis .claude/skills/sentiment-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "sentiment-analysis" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysis into .claude/skills/sentiment-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sentiment-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install majiayu000/claude-skill-registry sentiment-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analysis/sentiment-analysis .agents/skills/sentiment-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sentiment-analysis" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysis into .agents/skills/sentiment-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sentiment-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install majiayu000/claude-skill-registry sentiment-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analysis/sentiment-analysis .cursor/skills/sentiment-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sentiment-analysis" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysis into .cursor/skills/sentiment-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sentiment-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/majiayu000/claude-skill-registry.git --path skills/analysis/sentiment-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install majiayu000/claude-skill-registry sentiment-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analysis/sentiment-analysis .gemini/skills/sentiment-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sentiment-analysis" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysis into .gemini/skills/sentiment-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sentiment-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install majiayu000/claude-skill-registry sentiment-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analysis/sentiment-analysis .github/skills/sentiment-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sentiment-analysis" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysis into .github/skills/sentiment-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sentiment-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install majiayu000/claude-skill-registry sentiment-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analysis/sentiment-analysis .opencode/skills/sentiment-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sentiment-analysis" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/analysis/sentiment-analysis into .opencode/skills/sentiment-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sentiment-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sentiment-analysis- GitHub stars
- 666
- Used in
- 1 other repo
- Token cost
- ~875 tokens
- SKILL.md length
- 397 words
- Files
- 2
- Skills in repo
- 1,273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights.
- Works in 6 steps: Data Ingestion: Read all feedback… → Segment Identification: Identify at… → Thematic Analysis: Extract recurring… → …
- Analyzing user feedback at scale
- SKILL.md covers Purpose, Instructions and Best Practices
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Sentiment Analysis is an agent skill from majiayu000/claude-skill-registry. Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns.
Its SKILL.md is about 880 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).
It sits in Sales & Support, covering Customer feedback analysis and User stories. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.
When your agent uses it
- Analyzing user feedback at scale
- Running sentiment analysis on reviews
- Identifying satisfaction patterns
Example prompts
- “/sentiment-analysis”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Data Ingestion: Read all feedback sources and create a working inventory
- Segment Identification: Identify at least 3 distinct user segments or personas from the feedback
- Thematic Analysis: Extract recurring themes, pain points, and positive feedback per segment
- Sentiment Scoring: Assign sentiment scores (-1 to +1) for overall satisfaction per segment
- Impact Assessment: Prioritize insights by frequency, severity, and business impact
- Synthesis: Create segment profiles with consolidated insights
What it can do on your machine
Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
productcompass.pm
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Sentiment Analysis loads about 875 tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 397 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 397 words, ~875 tokens.
Download SKILL.mdSave it as
.claude/skills/sentiment-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- sentiment-analysis
- description
- Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns.
Sentiment Analysis
Purpose
Analyze large-scale user feedback data to identify market segments, measure satisfaction, and uncover product improvement opportunities. This skill synthesizes feedback into actionable insights organized by user segment, sentiment, and impact.
Instructions
You are an expert user researcher and feedback analyst specializing in qualitative data synthesis and sentiment analysis at scale.
Input
Your task is to analyze user feedback data for $ARGUMENTS and identify market segments with associated sentiment insights.
If the user provides CSV files, PDFs, survey responses, review data, social listening reports, or other feedback sources, read and analyze them directly. Extract patterns, themes, and sentiment signals from the data.
Analysis Steps (Think Step by Step)
- Data Ingestion: Read all feedback sources and create a working inventory
- Segment Identification: Identify at least 3 distinct user segments or personas from the feedback
- Thematic Analysis: Extract recurring themes, pain points, and positive feedback per segment
- Sentiment Scoring: Assign sentiment scores (-1 to +1) for overall satisfaction per segment
- Impact Assessment: Prioritize insights by frequency, severity, and business impact
- Synthesis: Create segment profiles with consolidated insights
Show full SKILL.md (214 more words)Show less
Output Structure
For each identified segment:
Segment Profile
- Name/identifier and common characteristics
- User count or proportion in feedback dataset
- Primary use case or context
Jobs-to-be-Done
- Core job this segment is trying to accomplish
- Associated desired outcomes
Sentiment Score & Satisfaction Level
- Overall sentiment score (-1 to +1)
- Key satisfaction drivers and detractors
- Net Promoter Score (NPS) proxy if applicable
Top Positive Feedback Themes
- What this segment loves about $ARGUMENTS
- Key strengths from user perspective
- Examples of successful use cases
Top Pain Points & Criticism
- Most frequent complaints or frustrations
- Unmet needs or missing features
- Friction points in user journey
- Direct quotes from feedback when available
Product-Segment Fit Assessment
- How well $ARGUMENTS serves this segment's needs
- Potential to improve fit through product changes
- Risk of churn or dissatisfaction
Actionable Recommendations
- 2-3 highest-impact improvements per segment
- Quick wins vs. strategic initiatives
- Segments to prioritize or de-prioritize
Best Practices
- Ground all findings in actual user feedback; cite sources
- Identify both majority and minority perspectives within segments
- Distinguish between feature requests and fundamental pain points
- Consider context and constraints users face
- Flag segments with small sample sizes or uncertain sentiment
- Look for cross-segment patterns and universal pain points
- Provide balanced view of product strengths and weaknesses
Further Reading
© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/analysis/sentiment-analysis of majiayu000/claude-skill-registry.
- SKILL.md
- metadata.json
Open the folder on GitHubat commit 2d14a69
Used in 1 other repository
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Sentiment Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sentiment Analysis this skillmajiayu000/claude-skill-registry | 666 | 1 repos | ~875 | Automated safety check: Pass | MIT | |
| Customer ResearchNexus-JPF/note-companion | 870 | 6 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Ideal Customer Profilephuryn/pm-skills | 27k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Review Analysisliangdabiao/amazon-sorftime-research-MCP-skill | 946 | 1 repos | ~2.5k | Automated safety check: Pass | None | |
| Bggg Data Amazonbinggandata/bggg-skills | 603 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Zsxqunnoo/zsxq-skill | 304 | — | ~3.8k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Sentiment Analysis
What does Sentiment Analysis do?
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Sentiment Analysis is an agent skill from majiayu000/claude-skill-registry. Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights.
When should I use Sentiment Analysis?
Sentiment Analysis fits situations like: analyzing user feedback at scale; running sentiment analysis on reviews; identifying satisfaction patterns.
How do I install Sentiment Analysis in Claude Code?
Run `npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a claude-code`. Or copy the skill folder (skills/analysis/sentiment-analysis in majiayu000/claude-skill-registry) into .claude/skills/sentiment-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Sentiment Analysis in Codex?
Run `npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a codex`. Or copy the skill folder (skills/analysis/sentiment-analysis in majiayu000/claude-skill-registry) into .agents/skills/sentiment-analysis in your project. Codex loads it when a task matches its description.
Can I use Sentiment Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill sentiment-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sentiment-analysis, .gemini/skills/sentiment-analysis, .github/skills/sentiment-analysis and .opencode/skills/sentiment-analysis in your project.
What does Sentiment Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Sentiment Analysis is instructions for the agent only.
Does Sentiment Analysis access the network?
SKILL.md names 1 domain. As links in the text: productcompass.pm. This is read from the text; nothing was executed.
Is Sentiment Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Sentiment Analysis use?
Sentiment Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Sentiment Analysis use?
About 875 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Sentiment Analysis?
Skills that share tags, products or a category with Sentiment Analysis: Customer Research (Nexus-JPF/note-companion, 870 stars), Ideal Customer Profile (phuryn/pm-skills, 27k stars), Review Analysis (liangdabiao/amazon-sorftime-research-MCP-skill, 946 stars) and Bggg Data Amazon (binggandata/bggg-skills, 603 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sentiment Analysis?
majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.
Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.