qlaris
Qlaris v1.0.8
User & prototype testing
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Description
From the marketplace listing
Validate product ideas in minutes, not weeks. qlaris brings user research into ChatGPT. Ask a product question and get evidence back in the same conversation: run surveys, customer interviews, focus groups, user testing and usability testing on your prototypes, or ask questions of the research your team has already added to qlaris. qlaris can also tell you when AI answers aren’t reliable enough: any question or finished study can be checked with a clear confidence verdict, and for questions that need real people, you can request research with human respondents straight from ChatGPT. What you can do with qlaris: - Prototype testing and usability testing: share a prototype and see where users get stuck, what confuses them and what they would change, before a single line goes to engineering. - User research surveys: test concepts, messaging, pricing and feature priorities with your target audience, consumer or B2B. - Customer interviews and focus groups: go deep on needs, motivations and objections in 1:1 interviews or group discussions. - Answers from your existing research: ask what your company already knows and get a sourced answer, checked for freshness and conflicting findings. - Real user research on demand: when a question needs human respondents, you can request it from the qlaris team without leaving the chat; a person follows up. Responses come from calibrated AI customer panels, so most studies return results in minutes, with no recruiting or scheduling. Built for product managers, product leaders, UX researchers and innovation teams who want to back every product decision with evidence.
Language: English · Automatically detected from descriptions.
Competitor profile
From the developer’s listing and package; capabilities are not independently tested. Package observed Nov 3, 2026.
Declared capabilities
- Draft surveys and interview studies from a research question
- Run surveys on digital-twin panels for 40 countries
- Run 1:1 interview studies and moderated focus groups
Declared limitations
- Buying units is out of scope: the plugin has no purchase or payment tools.
- A general question unrelated to research does not use Qlaris.
- A survey without an audience is not launched; the user is asked who to survey.
Review scenarios; not an exhaustive list.
Cost & access
The plugin does not sell anything or take payments in ChatGPT. Studies use validation units the user's Qlaris account already holds; units are obtained outside ChatGPT, through Qlaris directly.
Terms may have changed since this observation.
Starter prompt
with qlaris: show my personas
Keywords
Matches for “repo rate”
Exact text from the indicated source. A mention alone does not establish support for your task.
Publisher capabilities · listing
Draft surveys and interview studies from a research question Run surveys on digital-twin panels for 40 countries Run 1:1 interview studies and moderated focus groups Run user tests of a website or prototype Publish prototypes from attached files for user tests Read results, findings and quotes with links to each study Manage personas, workspaces and workspace context Ask questions of your team's research repository Check how far a research question or a finished study can be trusted Request research with real human respondents
Publisher full description
Validate product ideas in minutes, not weeks. qlaris brings user research into ChatGPT. Ask a product question and get evidence back in the same conversation: run surveys, customer interviews, focus groups, user testing and usability testing on your prototypes, or ask questions of the research your team has already added to qlaris. qlaris can also tell you when AI answers aren’t reliable enough: any question or finished study can be checked with a clear confidence verdict, and for questions that need real people, you can request research with human respondents straight from ChatGPT. What you can do with qlaris: - Prototype testing and usability testing: share a prototype and see where users get stuck, what confuses them and what they would change, before a single line goes to engineering. - User research surveys: test concepts, messaging, pricing and feature priorities with your target audience, consumer or B2B. - Customer interviews and focus groups: go deep on needs, motivations and objections in 1:1 interviews or group discussions. - Answers from your existing research: ask what your company already knows and get a sourced answer, checked for freshness and conflicting findings. - Real user research on demand: when a question needs human respondents, you can request it from the qlaris team without leaving the chat; a person follows up. Responses come from calibrated AI customer panels, so most studies return results in minutes, with no recruiting or scheduling. Built for product managers, product leaders, UX researchers and innovation teams who want to back every product decision with evidence.
Files & skills
File archives
Skill instructions
help-with-qlaris5.65 KB
---
name: help-with-qlaris
description: MANDATORY router — whenever the user message contains "with qlaris" (any casing, with or without a colon or arguments, e.g. "with qlaris: <goal>", "with qlaris: how do I …", or "with qlaris:" alone), you MUST load and follow this skill BEFORE responding; never answer a "with qlaris" request from memory. Also use when the user asks how to do anything with qlaris — creating personas or running research (surveys, UX tests, interviews). The command menu and router for everything qlaris.
---
# With qlaris
## Behavior — how to handle a request
- **`with qlaris: <a goal>`** → do it. For research, pick the audience, run the study, and deliver
the findings — asking first when the goal is large or unclear. Use any detail the user added
(audience, sub-questions, approach, exact output); leave the rest open and decide sensibly.
- **`with qlaris: how do I …`** → explain and point to the right tool or skill — run nothing.
- **`with qlaris:`** (nothing after) → print the **Cheat sheet** below **verbatim**.
Match the user's language, check cost with a `dryRun` before anything large, and only report results
once they are final. For "how do I" questions, don't execute write/action tools; read-only `list_*` /
`get_*` are always fine.
---
## Cheat sheet (print verbatim for a blank `with qlaris:`)
**CHEAT SHEET · COMMANDS**
# with qlaris
Everything starts with **`with qlaris:`** — say what you want and qlaris does it, or points you to
the right skill. Add as much or as little detail as you like: audience, sub-questions, approach,
exact output. Leave things out and qlaris fills the gaps sensibly or asks first.
### the basics — Three ways to ask
| say | what happens |
|---|---|
| `with qlaris: <research goal and specifications>` | qlaris does it. For research it picks the audience, runs the study and delivers the findings — asking first when the goal is large or unclear. You can also add any detail about the audience, research or similar, or leave it open and let qlaris decide. |
| `with qlaris: how do I …` | qlaris explains and points to the right tool or skill — nothing is run. |
| `with qlaris:` | Shows this cheat sheet. |
qlaris matches your language, checks cost with a dry run before anything large, and only reports
results once they are final.
### personas — Build and reuse audiences
| say | what happens |
|---|---|
| `with qlaris: create a persona <description>` | Build a research persona from a short description. |
| `with qlaris: list my personas` | Show existing personas to reuse. |
### research — Say your question, qlaris handles the rest
| say | what happens |
|---|---|
| `with qlaris: <your research question>` | qlaris chooses the audience, runs the study and compiles the findings. |
| `with qlaris: run a survey <survey specifications>` | Quantitative survey on a digital-twin panel. |
| `with qlaris: run a UX test <UX test specifications>` | Twins navigate a URL and report their experience. |
| `with qlaris: run an interview <interview specifications>` | One-to-one interview study: a decision, 2–5 research questions, a discussion guide, one audience (or up to five to compare), 3–50 interviews and a report. Free draft first; you approve before anything is paid. |
Want control? State any preference as text — audience, specific personas, exact questions, method,
sample size — and it is used instead of chosen for you.
Two ways to phrase the same command:
- **Quick:** "with qlaris: Find out if Americans prefer chocolate or vanilla ice cream when going to the cinema."
- **Steered:** "with qlaris: Should a new US cinema chain mainly sell ice cream, and which flavor? Focus on the western USA, under 45. Detailed report, qualitative through quantitative. Ask clarifying questions first."
### tips — Getting good results
- Say the decision, not just a topic. "Should we charge for X?" beats "ask about pricing".
- Be as specific or as hands-off as you like. Name the audience and questions, or leave them to qlaris.
- Personas read best as short narratives. Don't over-define — open traits keep the panel real.
---
## Under the hood (for routing)
- **Personas:** `create_persona({ country, description, directPrompt })` (pass the narrative to both
`description` and `directPrompt`); reuse via `list_personas` / `get_persona`.
- **Survey:** `run_survey` — target via `personaId` / `filters` / `segmentSlug` / `groups`; question
types via `list_question_types`; `dryRun` for cost; poll `get_survey_status` → `get_survey_results`.
- **UX test:** `run_user_test` (needs `url` + `task`; host a design first with `serve_prototype`);
poll `get_user_test_status` → `get_user_test_results`.
- **Interview (1:1 study):** `draft_interview_study` (FREE — ask the decision; omit `researchQuestions`
and `guide` and qlaris proposes and drafts them; confirm the audience; show `proposals`, `coverage`,
`validity`, `costBar`; put `questionsForUser[]` to the user; follow `nextSteps[]`; apply edits to
`draft.study`; follow `draft.procedure`) → `run_interview_study` with `{ study: draft.study, requestId }`
(`study.pilot: true` when the sample is ≥ 6 and the user wants to read three first) → poll
`get_interview_study` at `suggestedPollIntervalSeconds` → `report.markdown` rendered AS RETURNED,
every finding with its validity label. Transcripts: `get_interview_study` with a `participantId`.
Cancel / regenerate / launch the remainder: `cancel_interview_study` / `regenerate_interview_report` / `launch_interview_study_remainder`.
- **Rule:** for "how do I …" questions, explain and point — don't run write/action tools. For a
stated research goal, run it. Read-only `list_*` / `get_*` are always fine.
Release notes
First version.
Declared in the saved package. Remote tools may change independently.
Package details
Publisher declarations from the archived package. These are separate from our research and the live service's terms.
- Package author
- Qlaris
- Keywords
- See keywords
- Declared availability
- AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IL, IS, IT, LT, LU, LV, ME, MK, NL, NO, PL, PT, RO, RS, SE, SI, SK, TR, UA, USDeclared regions; live availability may differ.
- Commerce declaration
- Does not support commerceThis does not establish whether access is free or paid.
- Review scenarios
- 5 positive · 3 negativeScenario counts, not test results.
Declared capabilities
- Draft surveys and interview studies from a research question
- Run surveys on digital-twin panels for 40 countries
- Run 1:1 interview studies and moderated focus groups
- Run user tests of a website or prototype
- Publish prototypes from attached files for user tests
- Read results, findings and quotes with links to each study
- Manage personas, workspaces and workspace context
- Ask questions of your team's research repository
- Check how far a research question or a finished study can be trusted
- Request research with real human respondents
Package observed Nov 3, 2026.
Technical details
- First seen
- Oct 28, 2026 · 12:00 UTC
- Last seen
- Nov 3, 2026 · 18:00 UTC
- Collection status
- Collected
plugin_asdk_app_6ad1d805d7c88191bed20db623cb5763
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