Agentic user research at scale

MCP connector

Server URL

https://api.evermuse.com/api/mcpCopy

Login

OAuth

Skills

43 in the Claude listing

• Analyze feature requestsTriage a pile of customer feature requests into themes, merge duplicates, and surface the underlying need behind each ask — pulling the requests straight from Evermuse notes and backing every theme wi
• assumptionsSurface the risky assumptions behind a feature or idea, but first check the evidence — if customers already answered it, it's a finding, not an assumption — then score the rest by Impact × Risk and ma
• Beachhead segmentPick the first beachhead market segment by measuring which segment's people show up most and most painfully in real customer evidence, then evaluating it on burning pain, willingness to pay, winnable
• Brainstorm ideasGenerate product ideas from PM, Designer, and Engineer perspectives — seeded by the real unmet needs customers actually voiced — and return an idea→evidencing-quote mapping.
• Brainstorm okrsDraft team-level OKRs — inspirational objectives with measurable key results — where each objective maps to an evidenced customer outcome and each key result measures reduction of a real, stated custo
• Business modelBuild a Business Model Canvas — all 9 blocks — with the problem and customer-segment boxes grounded in real customer evidence and the channel/competition boxes grounded in market context.
• Competitive battlecardCreate a sales-ready competitive battlecard against a named competitor where the 'they say / we say' rows are ACTUAL objections and competitor mentions pulled from real customer conversations — not in
• Competitor analysisAnalyze competitors and find differentiation openings by cross-checking capability data against what customers ACTUALLY say about each rival — mentions, win/loss reasons, switching pain — with quotes.
• Create prdCreate a business Product Requirements Document from an 8-section template — problem, objectives, segments, value propositions, solution, release — grounded in real customer evidence (verbatim quotes,
• Customer journey mapMap the end-to-end customer journey — awareness through advocacy — with the real pain point, emotion, and a verbatim customer quote at each stage, plus prioritized fixes.
• Customer researchAnswer questions about what customers actually think, need, ask for, or complain about — by searching real customer evidence in Evermuse and returning a quote-rich, source-linked brief.
• Deep diveDive deep into one topic the user cares about — first ask what's top-of-mind, then answer it with a quote-rich, source-linked brief grounded in real customer evidence from the Evermuse Mock Data corpu
• Development planCreate a development plan for a feature that starts from what customers actually requested — Evermuse quotes and demand evidence carried into the plan itself — then applies spec-driven phasing and a d
• Gap analysisAudit an existing spec, plan, or shipped feature for gaps across three lenses — spec-vs-spec consistency, spec-vs-code implementation, and whether the build covers what customers need — with every fin
• Gtm strategyBuild a go-to-market strategy — messaging, channels, segment focus, GTM motions, metrics, and a launch timeline — where every choice is anchored in real customer evidence, not guesswork.
• Ideal customer profileBuild an Ideal Customer Profile from your real won-and-happy customers — firmographics, behaviors, jobs-to-be-done, and pains drawn from actual conversations with the accounts that bought and stayed.
• Initial reportPresent the first Evermuse report after the initial source scan - Use right after ingestion completes, when the user picks "Get my initial report", runs find_skills:initial-report, or asks 'show me my
• Interview scriptWrite a Mom-Test customer interview guide — warm-up, JTBD exploration, wrap-up — but first check the evidence for what's ALREADY known so the questions target the open gaps instead of re-asking answer
• List capabilitiesShow the user everything Evermuse can do — announce it in chat, then render the interactive list-capabilities picker of every agentic skill, grouped by category, and wait for them to pick one.
• Market sizingEstimate market size (TAM, SAM, SOM) with top-down and bottom-up approaches, grounded in market/industry signals and validated against a real customer beachhead.
• North star metricDefine a customer-centric North Star Metric plus a tree of 3-5 input metrics that drive it, where the North Star is anchored to the actual value customers describe getting from the product in real evi
• Opportunity solution treeBuild a Teresa Torres Opportunity Solution Tree — outcome → opportunities → solutions → experiments — where every opportunity node is backed by a real customer quote and unsupported nodes are flagged
• Outcome roadmapTransform a feature-list (output) roadmap into an outcome-focused one — each lane rewritten as 'Enable [segment] to [outcome] so that [business impact]' and citing the demand evidence behind it, groun
• Positioning and messagingGenerate differentiated positioning options and campaign/message ideas written in your customers' own mined vocabulary, where every message maps to a real quote that proves it resonates.
• Pricing strategyDesign pricing and monetization grounded in real willingness-to-pay signals, pricing objections, and value language from customer evidence — with competitor pricing as a labeled secondary input.
• Prioritize featuresRank a backlog of feature ideas using real demand counts from customer evidence — Reach and Impact come from how many distinct accounts actually asked, not a gut number — and return a top-5 with the q
• Product strategyBuild a product strategy on the 9-section Product Strategy Canvas where every pillar is anchored in real customer evidence and market context, not guesswork.
• Product visionCraft an inspiring, achievable product vision anchored in customers' own words about the future they want — not internal aspiration alone.
• Release notesGenerate user-facing release notes / changelogs from tickets, PRDs, or git logs — organized by new features, improvements, fixes — with a 'You asked, we built' angle that finds the real customers who
• Review prReview a pull request against three things at once: code quality, the spec it was meant to satisfy, and the actual customer asks behind it — calling out where the diff diverges from what customers lit
• segmentationSegment a market or user base by evidence-based need differences — not demographics — into 3-5 distinct groups, each with its jobs-to-be-done, pains, product fit, and representative customer quotes.
• Sentiment analysisAnalyze the feedback corpus over a time period to surface sentiment, themes, and satisfaction shifts — with a score per theme and verbatim quotes carrying their own sentiment labels.
• Setup evermuseThis skill sets up the Evermuse MCP extension prototype inside your agentic app.
• Shipping artifactsGenerate the ship-readiness documentation set for an AI-built (vibe-coded) feature — architecture, flows, permissions, variables, and a tests coverage map, plus conditional docs — and reconstruct the
• Strategy frameworksRun a classic strategy framework — SWOT, PESTLE, Porter's Five Forces, or Ansoff Matrix — where every cell cites a real customer-evidence or market-context result instead of generic filler.
• Strategy red teamAdversarially attack a strategy, PRD, or roadmap by hunting the customer counter-evidence that falsifies its claims — 'you assume X, but three customers said the opposite'.
• Summarize conversationSummarize one customer interview or team meeting into structured notes — participants, needs/JTBD, verbatim quotes with timestamps, decisions, action items — by locating the conversation in Evermuse a
• Test scenariosCreate QA test scenarios in Given/When/Then form from a spec's acceptance criteria AND from the real edge cases customers actually hit — failure stories and complaints pulled from Evermuse so the test
• User personasBuild user personas from the real people in a company's customer corpus — 3 evidence-backed personas with jobs-to-be-done, pains, gains, and an 'in their own words' verbatim quote block each.
• User storiesBreak a feature into user stories (or job stories) — INVEST-shaped, 3-C's structure, each story citing the motivating customer quote and acceptance criteria that reflect what customers actually expect
• Using evermuseFoundational doctrine and mechanics for grounding product work in real customer evidence via the Evermuse MCP — loaded by every other Evermuse skill.
• Value propositionDesign a value proposition on the 6-part JTBD structure, then turn it into ready-to-use marketing/sales/onboarding statements — all in customers' verbatim language.
• Write feature specWrite a feature specification grounded in real customer evidence — verbatim quotes, needs, and pain points with source links from Evermuse — using spec-driven-development structure (prioritized user s