Customer Research
Nexus-JPF/note-companion
When the user wants to conduct, analyze, or synthesize customer research.
When the user wants to research customers from public communities, or synthesize customer language, pains, and objections.
Install Customer Research
$ npx skills add unifapi-agent/agents --skill customer-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install unifapi-agent/agents customer-research --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/unifapi-agent/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/content-strategy-agent/customer-research .claude/skills/customer-research && 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 "customer-research" agent skill from https://github.com/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-research into .claude/skills/customer-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-research", 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/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-researchType 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 unifapi-agent/agents --skill customer-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install unifapi-agent/agents customer-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/unifapi-agent/agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/content-strategy-agent/customer-research .agents/skills/customer-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "customer-research" agent skill from https://github.com/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-research into .agents/skills/customer-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-research", 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 unifapi-agent/agents --skill customer-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install unifapi-agent/agents customer-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/unifapi-agent/agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/content-strategy-agent/customer-research .cursor/skills/customer-research && 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 "customer-research" agent skill from https://github.com/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-research into .cursor/skills/customer-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-research", 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/unifapi-agent/agents.git --path skills/content-strategy-agent/customer-research--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 unifapi-agent/agents --skill customer-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install unifapi-agent/agents customer-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/unifapi-agent/agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/content-strategy-agent/customer-research .gemini/skills/customer-research && 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 "customer-research" agent skill from https://github.com/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-research into .gemini/skills/customer-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-research", 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 unifapi-agent/agents customer-researchInstalls 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 unifapi-agent/agents --skill customer-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/unifapi-agent/agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/content-strategy-agent/customer-research .github/skills/customer-research && 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 "customer-research" agent skill from https://github.com/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-research into .github/skills/customer-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-research", 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 unifapi-agent/agents --skill customer-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install unifapi-agent/agents customer-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/unifapi-agent/agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/content-strategy-agent/customer-research .opencode/skills/customer-research && 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 "customer-research" agent skill from https://github.com/unifapi-agent/agents/tree/main/skills/content-strategy-agent/customer-research into .opencode/skills/customer-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-research", 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
customer-research- GitHub stars
- 589
- Token cost
- ~2.1k tokens
- SKILL.md length
- 829 words
- Files
- 3 (incl. references)
- Skills in repo
- 47
- Repo updated
- First seen
- Licence
- MIT
At a glance
When the user wants to research customers from public communities, or synthesize customer language, pains, and objections.
- Works in 6 steps: Frame the research. If… → Pick the watering holes. Choose the… → Cluster by theme across sources, then… → …
- Wants to research customers from public communities
- SKILL.md covers Use UnifAPI for live evidence, Workflow, Output: research synthesis and Scoring & confidence, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Customer Research is an agent skill from unifapi-agent/agents. When the user wants to research customers from public communities, or synthesize customer language, pains, and objections. Also use on "customer research," "ICP research," "voice of customer," "VOC," "what do customers say," "what are customers struggling with," "Reddit mining," "review mining," "community research," "forum research," "build personas," "jobs to be done," "JTBD," "customer sentiment," or "find out why customers buy/churn." Pulls authentic language from public sources via UnifAPI to inform…
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `README.md` and `references/voc-method.md`).
It sits in Marketing & SEO, covering Market research and User stories. It works with Reddit and YouTube. The repository describes itself as: Open-source marketing agents for Claude, ChatGPT, Codex, OpenClaw & Hermes. One plugin: SEO audits, GEO / AI-visibility, local SEO, KOL pricing, social listening & competitive… The licence is MIT.
When your agent uses it
- Wants to research customers from public communities
- Synthesize customer language
Example prompts
- “customer research,”
- “ICP research,”
- “voice of customer,”
- “/customer-research”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Frame the research. If .agents/product-marketing.md (or .claude/product-marketing.md) exists, read it first. Establish the goal (messaging…
- Pick the watering holes. Choose the sources that match the ICP, then pull verbatim items: Reddit threads (via seo/serp site:reddit.com →…
- Cluster by theme across sources, then score each theme by frequency × intensity (how often it appears × how emotionally it's expressed)…
- Label confidence on every theme: High = 3+ independent sources, unprompted, consistent across segments; Medium = 2 sources or one segment…
- Pull 5–10 "money quotes" per theme — verbatim, with source URL and date, ready to drop into copy.
- Check for sample bias. Reddit and TikTok skew toward power users and strong opinions — factor that in before generalizing. Don't build a…
What it can do on your machine
Read from SKILL.md and the folder at commit fb53247. 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 (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Customer Research loads about 2.1k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 166 tokens; SKILL.md has 829 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 unifapi-agent/agents at commit fb53247, republished under its MIT licence (© unifapi-agent). 829 words, ~2,125 tokens.
Download SKILL.mdSave it as
.claude/skills/customer-research/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- customer-research
- description
- When the user wants to research customers from public communities, or synthesize customer language, pains, and objections. Also use on "customer research," "ICP research," "voice of customer," "VOC," "what do customers say," "what are customers struggling with," "Reddit mining," "review mining," "community research," "forum research," "build personas," "jobs to be done," "JTBD," "customer sentiment," or "find out why customers buy/churn." Pulls authentic language from public sources via UnifAPI to inform messaging and content. For turning the findings into topics, see content-opportunity-brief. For writing copy from them, see copywriting.
- license
- MIT
- metadata.author
- UnifAPI
- metadata.version
- 1.0.0
- metadata.adapted_from
- https://github.com/coreyhaines31/marketingskills
- metadata.adapted_author
- Corey Haines
Customer Research
You are an expert customer researcher. Your goal is to uncover what customers actually think, say, and struggle with — in their own words — so messaging and content are grounded in reality rather than assumption. You gather that language from public communities where people speak without a filter, and tie every insight to the source it came from.
This is an enhanced skill: it reads live public data through UnifAPI.
Use UnifAPI for live evidence
The original ran two modes — analyze existing assets through the Jobs / Pains / Triggers / Outcomes / Language / Alternatives frame, and do "digital watering-hole" research. The watering holes were manual. Here you mine the actual communities live, so the persona is built from quotes you can cite, not invented. Use the unifapi skill to connect (OAuth MCP), then call:
- Verbatim VOC from Reddit (no keyword search) — run
seo/serpforsite:reddit.com <problem/topic>to find threads, thenreddit/posts/{id}/commentsto pull pains, triggers, outcomes, objections, alternatives, and exact phrasing from upvoted comments. Profile the community withreddit/subreddits/{name}and trace a vocal author withreddit/users/{username}/commentsto see if a pain is one person or a pattern. - Short-form / consumer voice —
tiktok/searchto find creators on the problem space, thentiktok/videos/{id}/commentsfor reaction language and "I wish it could…" unmet needs. - Trigger events & market framing —
news/searchfor the launches, funding, and shifts that prompt people to start looking, with publish dates. - Which pains are widespread —
seo/keywords/ideasfor the question keywords people type ("how do I X," "why does X") — a high-volume question is a verbatim signal that a pain is common, not a one-off. - Topic interest (titles only, NOT comments) —
youtube/searchto gauge which framings of the problem pull views via titles, descriptions, view/like counts, andyoutube/videos/{id}/related. YouTube exposes no comment endpoint here — use it for topic/title signal, never promise comment mining.
UnifAPI reads public data only — it never accesses a user's private CRM, email, support tickets, or accounts; use a connector platform for those. Keep any billing metadata so the output can state record cost.
Workflow
- Frame the research. If
.agents/product-marketing.md(or.claude/product-marketing.md) exists, read it first. Establish the goal (messaging / personas / churn / objections), the target segment, and the deliverable wanted. - Pick the watering holes. Choose the sources that match the ICP, then pull verbatim items: Reddit threads (via
seo/serpsite:reddit.com→reddit/posts/{id}/comments), TikTok comments (tiktok/videos/{id}/comments), news triggers (news/search), and question keywords (seo/keywords/ideas). For each item capture: source URL + date, verbatim quote, what prompted it, sentiment, theme tag (pain / trigger / outcome / objection / alternative / language), and any profile signals. - Cluster by theme across sources, then score each theme by frequency × intensity (how often it appears × how emotionally it's expressed). The full extraction and clustering procedure is in references/voc-method.md.
- Label confidence on every theme: High = 3+ independent sources, unprompted, consistent across segments; Medium = 2 sources or one segment; Low = single source, needs validation. Weight the last 12 months more heavily.
- Pull 5–10 "money quotes" per theme — verbatim, with source URL and date, ready to drop into copy.
- Check for sample bias. Reddit and TikTok skew toward power users and strong opinions — factor that in before generalizing. Don't build a persona from fewer than ~5 independent data points per segment; leave persona fields blank rather than invent them.
Show full SKILL.md (291 more words)Show less
Output: research synthesis
Pick the deliverable(s) the user needs.
# Customer Research — <segment> — <date>
Sources checked: Reddit (via site:reddit.com SERP), TikTok comments, News, SEO question keywords, YouTube titles. Date range: <range>.
## Themes (ranked by frequency × intensity)
| Theme | Type | Freq×Int | Confidence | Representative verbatim (source + date) | Implication |
| ----------------------------- | ---- | -------- | ---------- | ------------------------------------------------ | ----------------------- |
| "setup takes a whole weekend" | pain | 5×4 | High | "spent two days just wiring it up" — r/… 2026-03 | lead with time-to-value |
## VOC quote bank (5–10 verbatim per theme, source + date on each)
- pain · "spent two days just wiring it up" — reddit.com/… 2026-03
## Persona (only fields the data supports; leave blanks rather than invent)
Persona: <role / segment>
Jobs-to-be-done: …
Trigger events: …
Top pains (with confidence): …
Desired outcomes: …
Objections / blockers: …
Alternatives considered: …
Key vocabulary (their words): …
Evidence base: N independent sources, date range …Optionally add Competitive intelligence — what the community says about competitors vs. the brand, with quotes.
Scoring & confidence
Rank themes by frequency × intensity, then carry the confidence label as a separate, honest signal (a frequent theme from one segment can still be Medium confidence):
| Frequency (how often it recurs) | Intensity (how strongly it's expressed) | |
|---|---|---|
| 1 | once or twice | neutral / matter-of-fact |
| 3 | recurs across a few threads | clear frustration or enthusiasm |
| 5 | dominant, across sources | visceral — "I hate," "lifesaver," switching away |
| Confidence | Rule |
|---|---|
| High | 3+ independent sources, unprompted, consistent across segments |
| Medium | 2 sources, or strong but within a single segment |
| Low | single source — flag as "needs validation," never present as fact |
Full procedure (capture rows, tag taxonomy, clustering, worked examples) lives in references/voc-method.md.
Guardrails
- Read-only ("eyes, not hands"); public communities only. It briefs from public data; it does not write or publish. The research is the deliverable — the operator's own assistant turns it into copy or content.
- Confirmed vs. inferred: quote real sources verbatim and cite them; don't paraphrase into something the person didn't say, and never fabricate quotes or personas. Leave persona fields blank rather than invent them.
- Public-community signal is directional and biased toward vocal users — present confidence levels and dated snapshots, not certainty. State sample bias before generalizing.
- UnifAPI reads public data only; it cannot see private interviews, surveys, or support tickets. If the user has those, analyze them separately and combine with the public findings.
Related Skills
- content-opportunity-brief (Content Strategy Agent): turn the discovered pains and questions into ranked, evidence-backed content topics.
- content-strategy (Content Strategy Agent): feed this research into pillar selection and messaging.
- unifapi: the shared data skill — connect MCP and discover the Reddit/TikTok/News/SEO/YouTube operations this research reads.
© unifapi-agent, 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 2 other files (references) in skills/content-strategy-agent/customer-research of unifapi-agent/agents.
- SKILL.md
- README.md
- references/voc-method.md
Open the folder on GitHubat commit fb53247
Compare with similar skills
Customer Research 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 |
|---|---|---|---|---|---|---|
| Customer Research this skillunifapi-agent/agents | 589 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Customer ResearchNexus-JPF/note-companion | 870 | 6 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Comment MiningScrapeCreators/social-media-research-skills | 3.4k | — | ~1k | Automated safety check: Notes | MIT | |
| Blog DiscourseAgriciDaniel/claude-blog | 2.3k | 1 repos | ~3.4k | Automated safety check: Warn | MIT | |
| Trend DiscoveryScrapeCreators/social-media-research-skills | 3.4k | — | ~789 | Automated safety check: Notes | MIT | |
| Influencer Discoverytigerless-labs/influencer-discovery | 212 | — | ~2.5k | Automated safety check: Notes | None |
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Related
Questions about Customer Research
What does Customer Research do?
When the user wants to research customers from public communities, or synthesize customer language, pains, and objections. Customer Research is an agent skill from unifapi-agent/agents. When the user wants to research customers from public communities, or synthesize customer language, pains, and objections.
When should I use Customer Research?
Customer Research fits situations like: wants to research customers from public communities; synthesize customer language.
How do I install Customer Research in Claude Code?
Run `npx skills add unifapi-agent/agents --skill customer-research -a claude-code`. Or copy the skill folder (skills/content-strategy-agent/customer-research in unifapi-agent/agents) into .claude/skills/customer-research in your project. Claude Code loads it when a task matches its description.
How do I install Customer Research in Codex?
Run `npx skills add unifapi-agent/agents --skill customer-research -a codex`. Or copy the skill folder (skills/content-strategy-agent/customer-research in unifapi-agent/agents) into .agents/skills/customer-research in your project. Codex loads it when a task matches its description.
Can I use Customer Research 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 unifapi-agent/agents --skill customer-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/customer-research, .gemini/skills/customer-research, .github/skills/customer-research and .opencode/skills/customer-research in your project.
What does Customer Research need to run?
SKILL.md names no scripts, command-line tools or credentials: Customer Research is instructions for the agent only.
Does Customer Research access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Customer Research 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 Customer Research use?
Customer Research is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Customer Research use?
About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.
What are the alternatives to Customer Research?
Skills that share tags, products or a category with Customer Research: Customer Research (Nexus-JPF/note-companion, 870 stars), Comment Mining (ScrapeCreators/social-media-research-skills, 3.4k stars), Blog Discourse (AgriciDaniel/claude-blog, 2.3k stars) and Trend Discovery (ScrapeCreators/social-media-research-skills, 3.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Customer Research?
unifapi-agent (a GitHub organization) maintains it in unifapi-agent/agents, which has 589 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on September 5, 2026.
Source: unifapi-agent/agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.