| name | sales-askmore |
| description | AskMore (askmore.ai) platform help — a self-serve AI-moderated interview tool that runs asynchronous text/chat interviews via a share link: the AI adapts to each answer, follows up, and digs deeper (the survey-to-interview bridge), works in any language with auto-translation, and returns shareable reports with full transcripts. Bring your own participants (no built-in panel); pay-as-you-go credits with free credits to start. Use when setting up AskMore interviews for user/customer/market research, sizing its credit pricing and free credits, running multilingual interviews, sharing a participation link to your own audience, getting data out when there is no public API, or choosing AskMore vs Chikka / Frank / User Intuition. Do NOT use for the validate-before-building method (use /sales-idea-validation), an API/webhook/MCP interview pipeline (use /sales-userintuition), or analyzing existing feedback into themes (use /sales-customer-feedback). |
| argument-hint | [describe what you need help with in AskMore] |
| license | MIT |
| version | 1.0.0 |
| tags | ["sales","pre-launch","platform"] |
AskMore Platform Help
AskMore (askmore.ai) runs AI-moderated interviews on real people — you set an objective, and its AI
interviewer runs asynchronous, mostly text/chat interviews via a share link: it adapts to each answer,
follows up, and digs deeper the way a human researcher would, then delivers shareable reports
(key findings + full transcripts). It markets itself as the middle ground between a survey and an
interview — "as easy as sending a survey link," but with an AI that probes instead of a static form. It
works in any language (auto-translates questions, answers, and the report), so a respondent can answer
in their language and you read the synthesis in yours.
Its niche in the real-human AI-moderated-interview cluster (User Intuition, Strella, Voicepanel, Frank,
Chikka, Listen Labs) is three things:
- The survey↔interview bridge, text-first. The lowest-friction, most survey-like format in the cluster
— async, written answers, no scheduling, no call — vs the voice-first peers (Chikka, Frank, Voicepanel).
It's the pick when you want interview depth at survey reach and simplicity.
- Bring-your-own-participants, self-serve, pay-as-you-go. No built-in panel — you share a link with
your own audience/list (like Frank/Chikka). Billing is credits (free credits to start, then credit
packs), so a solo maker can sign up and run interviews today — the opposite of sales-gated peers.
- Any-language interviews + auto-translation built in, so it fits international/multi-market research.
Two things to say almost every time:
- It's real people, but a stated "I'd pay" is still not a purchase. Real interviews beat synthetic
signal (genuine reasoning, objections, language) — but the willingness-to-pay go/no-go belongs to a
real behavior test (pre-sale, smoke test), not an interview transcript. Route that to
/sales-idea-validation.
- It's UI-only — no public API, webhooks, or MCP surfaced. Distribution is a share link; data-out
is manual export of transcripts/reports. "Call the AskMore API / fire a webhook on completion" is the
wrong mental model — for a real pipeline, route to
/sales-userintuition.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
Ask only what you can't infer:
- What do you want from AskMore?
- A) Run new interviews — set an objective + questions, share the participation link, let the AI interview
- B) Recruit / reach participants — AskMore has no panel; you bring your own audience (email list, in-app, community)
- C) Read / export results — reports, key findings, full transcripts (there is no API/webhooks)
- D) Pricing / credits — free credits, credit packs, what a credit buys
- E) Choose — AskMore vs Chikka / Frank / User Intuition / Strella / Voicepanel
- F) Multilingual research — interview in any language + auto-translation
- Is this discovery (strangers) or feedback from your own users/customers? AskMore has no panel, so for
strangers you must recruit them elsewhere first — that changes the plan.
Skip-ahead: if the user wants to compare research tools across the market or the
validate-before-building method, that's a /sales-idea-validation question — route in Step 2.
Step 2 — Route or answer directly
| If the user's question is about… | Route to |
|---|
| Comparing research/idea/synthetic tools across the market, or the validate-before-building method | /sales-idea-validation {question} |
| A REST API / webhook / MCP-native interview pipeline (AskMore has none — it's UI-only) | /sales-userintuition {question} |
| Running a real behavior demand test (smoke-test page, waitlist, pre-sale) after interviews | /sales-idea-validation or /sales-funnel {question} |
| Analyzing existing NPS/CSAT/VoC/interview data into themes (post-collection, not new interviews) | /sales-customer-feedback or /sales-trill {question} |
| Synthetic-persona interviews (AI personas instead of real people) | /sales-syntheticusers or /sales-ditto {question} |
| A voice-first AI interviewer, or turning interviews into testimonials/case studies | /sales-chikka {question} |
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer AskMore-specific questions using Step 3.
Step 3 — AskMore reference
Read references/platform-guide.md for the full reference — the module/automation-surface table
(what's UI-only vs export), best-effort credit pricing and free-credit limits, the
Project → Interview → Report data model, the share-link distribution workflow, the any-language/translation
workflow, and how the AI's adaptive follow-ups work. Read references/askmore-api-reference.md for the
automation surface — it documents that there is no public API/webhooks/MCP and inventories the actual
data-out options.
Answer using only the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
- Say the caveat: a real interview is not a purchase. Whatever the user asks, make explicit that
AskMore interviews real people (a big step up from synthetic personas — genuine reasoning,
objections, language), but a stated "I'd pay" in an interview is not observed demand. Point the user
to the transcripts and key findings for objections and pricing language rather than trusting the
top-line summary as a verdict, then take the go/no-go from a real behavior test (pre-sale, smoke
test) — route that to
/sales-idea-validation.
- Treat automation as UI-only, and don't invent endpoints. When any automation/export/integration
comes up, state that AskMore has no public REST API, webhooks, or MCP server — distribution is a
share link and data-out is manual export of transcripts/reports. Don't design a REST/webhook
pipeline or guess endpoints; if a programmatic pipeline is a hard requirement, route to
/sales-userintuition. Present the no-API finding as best-effort — confirm at askmore.ai.
- Set expectations on recruiting: there is no panel. AskMore does not supply respondents — you
bring your own audience and share the link. It's the right tool when you already have people to talk to
(your users, list, or community) and the wrong tool for reaching strangers at scale; for a panel,
point to a panel-native peer via
/sales-idea-validation.
- Size it by credits, not seats, and call pricing best-effort. Billing is pay-as-you-go credits
(free credits to start, then credit packs) — a credit is roughly per completed interview/response.
Present every figure as best-effort and point to askmore.ai/pricing to confirm the current
credit rate, since the live site changes.
- Lean into its real edge: survey-simplicity with interview depth, in any language. Recommend it when
the user wants async, written, adaptive interviews their audience can answer on their own time, in
their own language — that's where AskMore beats both a static survey and a scheduling-heavy voice tool.
If you discover a gotcha or tip not in references/learnings.md, append it there with today's date.
Gotchas
Best-effort from research (2026-07) — the live site was bot-blocked at research, so credit pricing, free-credit
limits, the language list, whether a voice mode exists, and the exact export options all move; verify at
askmore.ai and askmore.ai/pricing.
- Real ≠ demand. Interviews reveal the why better than any synthetic tool, but a stated intent to
pay is not a purchase — the go/no-go still belongs to a real behavior test (pre-sale, smoke test).
- No public API/webhooks/MCP surfaced — automation is manual export. Don't design a
webhook-on-completion pipeline or invent endpoints; a REST/webhook pipeline is a
/sales-userintuition job.
Present this as best-effort (no API was documented anywhere at research).
- No built-in panel. AskMore doesn't recruit respondents — you bring your own audience via a share link.
For strangers at scale, recruit them elsewhere first (see
/sales-idea-validation).
- Credit pricing, not subscription seats. Free credits get you started; past that you buy credit packs
(roughly per interview/response). Historical aggregator figures (e.g. a small pack for a low double-digit
price) are stale — confirm the current rate at askmore.ai/pricing.
- It's text-first / async, not a live voice call. Respondents answer in writing on their own time.
If the user specifically needs voice depth or a testimonial pipeline, that's a
/sales-chikka job.
- "Any language" is a real strength, but check the report language. Respondents can answer in their
language and it auto-translates — confirm the synthesis/report language matches what your stakeholders read.
- It collects, it doesn't synthesize what you already have. AskMore runs new interviews; to theme
transcripts/open-ends you already have, use
/sales-trill or /sales-customer-feedback.
Related skills
/sales-idea-validation — The tool-agnostic validate-before-building method + the full research/persona/validator tool landscape (use this to decide build-or-not; an interview "yes" is not demand). Install: npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code/sales-chikka — The voice-first, self-serve real-human peer (AI agent "Ava" runs multilingual voice interviews + a VoiceVerify testimonial/case-study pipeline); pick Chikka for voice depth and marketing assets, AskMore for async text simplicity. Install: npx skills add sales-skills/sales --skill sales-chikka -a claude-code/sales-frank — The other bring-your-own-customers, self-serve, UI-only peer (Prelaunch.com; voice + chat, voice-minute-metered); closest analog to AskMore's BYO-participant model — pick by modality and pricing shape. Install: npx skills add sales-skills/sales --skill sales-frank -a claude-code/sales-researchgoat — The end-to-end, voice-first self-serve peer (researchgoat.com) that bundles AI research design + a screener + built-in participant recruitment + AI synthesis around live voice interviews; pick ResearchGOAT for voice depth + a design/recruit stack, AskMore for async written survey-reach. Install: npx skills add sales-skills/sales --skill sales-researchgoat -a claude-code/sales-userintuition — The REST-API/webhook/MCP real-human interview peer — the pick when you need a programmatic pipeline AskMore's UI-only surface can't offer. Install: npx skills add sales-skills/sales --skill sales-userintuition -a claude-code/sales-customer-feedback — Real-customer NPS/CSAT/VoC strategy across tools (use to analyze existing feedback; AskMore proactively runs new interviews). Install: npx skills add sales-skills/sales --skill sales-customer-feedback -a claude-code/sales-do — Not sure which skill to use? The router matches any sales objective to the right skill. Install: npx skills add sales-skills/sales --skill sales-do -a claude-code
Examples
Example 1: "The AskMore interviews loved my idea — should I build it?"
User says: "I sent an AskMore interview link to 20 people on my list and almost everyone said they'd use and pay for it. Green light?"
Skill does: Credits the signal as real (actual people, genuine reasoning — far better than a
synthetic tool), then draws the line: a stated "I'd pay" in an interview is not a purchase. Tells the
user to mine the transcripts and key findings for objections, hesitation, and pricing language (the
real value), then take the go/no-go from a real behavior test (pre-sale or a "buy" click) via
/sales-idea-validation. Notes credit pricing/limits are best-effort.
Result: The founder keeps the qualitative depth and runs a pre-sale before committing to build.
Example 2: "How do I pipe AskMore transcripts into my CRM/warehouse via the API?" (developer/automation)
User says: "I want a webhook to fire when an AskMore interview finishes and push the transcript to BigQuery."
Skill does: States plainly that AskMore has no public REST API, webhooks, or MCP server surfaced at
research — so there is no endpoint or key to build against, and it does not invent one (presenting the
finding as best-effort, confirm at askmore.ai). Explains distribution is a share link and the only
data-out is manual export of transcripts/reports. For a webhook-on-completion pipeline into a CRM or
warehouse, routes to /sales-userintuition (REST API + HMAC-signed webhooks + MCP).
Result: The user stops hunting for an API that doesn't exist and either exports manually or moves the pipeline to an API-native tool.
Example 3: "How much does AskMore cost and how do I reach people who aren't on my list?"
User says: "I want to interview target customers I don't already have contact with — what will AskMore cost me?"
Skill does: Explains AskMore is pay-as-you-go credits (free credits to start, then credit packs,
roughly per completed interview — all best-effort, confirm at askmore.ai/pricing), and flags the key
constraint: AskMore has no built-in panel, so it can't reach strangers — you share a link with an
audience you already have. To recruit unknown target customers, routes to /sales-idea-validation for the
panel-native tool map, then use AskMore (or a voice peer) to run the interviews.
Result: The user sizes credits correctly and recruits participants the right way instead of expecting AskMore to supply them.
Troubleshooting
"Where's the AskMore REST API / webhook to sync interviews?"
Symptom: You're looking for an API key and a webhook to fire on interview completion.
Cause: AskMore is UI-only — no public REST API, webhooks, or MCP server was documented anywhere at research. Distribution is a share link; data-out is manual export.
Solution: Export transcripts/reports from the UI. If a programmatic pipeline into a CRM/warehouse is a hard requirement, use an API-native tool instead — route to /sales-userintuition (REST API + HMAC-signed webhooks + MCP). Present the no-API finding as best-effort and confirm at askmore.ai.
"I don't have people to interview — does AskMore find respondents for me?"
Symptom: You expected AskMore to supply a panel of target customers.
Cause: AskMore has no built-in panel — it's bring-your-own-participants. You share the interview link with an audience you already have (list, in-app, community).
Solution: Recruit participants first (a panel marketplace or your own audience), then share the AskMore link. For the panel-native tool map, route to /sales-idea-validation.
"How many interviews do my free credits get me, and what happens after?"
Symptom: You're unsure what a credit buys and when you'll have to pay.
Cause: AskMore is pay-as-you-go credits — free credits to start, then credit packs; a credit is roughly per completed interview/response. Exact rates change and the live site was bot-blocked at research.
Solution: Treat all credit figures as best-effort and confirm the current rate and free-credit allotment at askmore.ai/pricing before planning a study; size the study by number of completed interviews, not seats.
