iMario (imario.ai) platform help — a synthetic-research "human layer" where reusable Synthetic Individuals (built from a plain-English brief, a LinkedIn profile, or a personality assessment, each with persistent working/episodic/semantic memory) run across six jobs on a visual Canvas: audience research, concept/product validation, sales-outreach and content testing, CX/journey design, sales-enablement rehearsal, and AI-agent personality via API. Use when setting up an iMario Canvas or Synthetic Individual, choosing how to build a cohort (brief vs LinkedIn vs personality twin), grounding it in a Knowledge Base, interpreting a synthetic report or the 90%-parity claim, reusing one persona across studies, wiring the Pro-gated API into a production agent, or judging whether a synthetic "yes" is real demand. Do NOT use for comparing synthetic-research/persona/idea tools or the validate-before-building method (use /sales-idea-validation), or the pure-play study tool with a public API (use /sales-syntheticusers).
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
iMario (imario.ai) platform help — a synthetic-research "human layer" where reusable Synthetic Individuals (built from a plain-English brief, a LinkedIn profile, or a personality assessment, each with persistent working/episodic/semantic memory) run across six jobs on a visual Canvas: audience research, concept/product validation, sales-outreach and content testing, CX/journey design, sales-enablement rehearsal, and AI-agent personality via API. Use when setting up an iMario Canvas or Synthetic Individual, choosing how to build a cohort (brief vs LinkedIn vs personality twin), grounding it in a Knowledge Base, interpreting a synthetic report or the 90%-parity claim, reusing one persona across studies, wiring the Pro-gated API into a production agent, or judging whether a synthetic "yes" is real demand. Do NOT use for comparing synthetic-research/persona/idea tools or the validate-before-building method (use /sales-idea-validation), or the pure-play study tool with a public API (use /sales-syntheticusers).
argument-hint
[describe what you need help with in iMario]
license
MIT
version
1.0.0
tags
["sales","pre-launch","platform"]
iMario Platform Help
iMario (imario.ai) is a synthetic-research and audience-intelligence platform that calls itself
"the human layer of AI." Instead of a one-shot study tool, its unit is a reusable Synthetic
Individual — a constrained cognitive model (not plain LLM roleplay) with a Deep Identity
narrative, Expert Reflection panels (demographer / psychologist / economist), Knowledge
Boundaries, and a three-layer memory (working / episodic / semantic, with Ebbinghaus decay) that
persists across sessions. You build a cohort three ways — a plain-English brief, a LinkedIn
profile, or a personality assessment ("synthetic twin") — and run tasks against them on a visual
Canvas (a node editor that replaced the old funnel flow), grounded in your own files via a
Knowledge Base (RAG). The same individual can be reused across six jobs: Discover (research),
Validate (concept/product), Launch (sales outreach & content testing), Optimize (CX/journey), Scale
(sales/service enablement), and Build (AI-agent personality via API).
Its signal is directional, not demand: synthetic individuals model existing/public/training data,
so they skew agreeable, generic, and Western-biased and can't surface a genuinely new unmet need.
The 90%+ "human parity" figure is a vendor claim — treat any synthetic result as a hypothesis to
disconfirm with real behavior, not a green light.
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 iMario?
A) Build a Synthetic Individual / cohort — pick the input (brief / LinkedIn / personality twin)
B) Set up a Canvas task — research, concept test, content test, journey, or sales rehearsal
C) Ground it in your own data (Knowledge Base / RAG upload) for specific answers
D) Interpret a synthetic report, distribution, or the 90%-parity claim you already have
E) Reuse one persona across multiple jobs, or automate via the Pro-gated API / production agent
F) Decide whether to trust it — is this a valid stand-in for real research?
A sharp brief + Knowledge Base yields usable signal;
a vague one yields generic filler.
What's the question and who's the audience?
Skip-ahead: if the user wants to compare synthetic-research/persona/idea 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 synthetic-research/persona/idea tools, or the validate-before-building method
/sales-idea-validation {question}
The pure-play synthetic study tool with a documented public REST API (Bearer, SDKs, SSE)
/sales-syntheticusers {question}
A data-grounded persona you chat with built from your GA4/CRM/social
/sales-delve or /sales-marketing-mary{question}
Running a real demand test (smoke-test page, waitlist, pre-sale) after synthetic signal
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer iMario-specific questions using Step 3.
Step 3 — iMario platform reference
Read references/platform-guide.md for the full reference — the Synthetic Individual model
(Deep Identity, Expert Reflection, Knowledge Boundaries, three-layer memory), the three cohort inputs,
the Canvas node editor and six jobs, Knowledge Base / RAG grounding, the API/webhook/UI-only tag on each
module, best-effort credit-based pricing and the Pro API gate, the data model (Synthetic Individual /
Canvas / Task / Cohort JSON shapes), and quick-start recipes.
For the API surface (Pro-gated, no public developer docs at research time), read
references/imario-api-reference.md.
Answer using only the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
You no longer need the platform guide — focus on the user's specific situation.
A synthetic "yes" is not demand — say so every time. Whatever the user asks, make explicit that
Synthetic Individuals model existing/public/training data, so they run agreeable, generic, and
Western-biased and can be confidently wrong. Frame every result as a hypothesis to disconfirm
with a real behavior test (smoke-test click, reply, pre-sale) — keep the objections, angles, and
language it surfaces (its real value), take the go/no-go from real strangers, and route the real test
to /sales-idea-validation.
Treat the "90%+ human parity" figure as a vendor claim, not proof. When the user cites it, note it
is self-reported (the site itself pegs quantitative agreement near ~89% and admits real survey retest
agreement is only ~93%), varies sharply by question type (weak on behavioral/emotional/cultural), and
is not a validity verdict — don't let it substitute for a real behavior test.
Play iMario's actual edge: reuse + memory. Its differentiator over one-shot tools is that the
same Synthetic Individual persists across sessions and jobs — build a cohort once, then reuse it
across Discover → Validate → Launch → rehearsal on the Canvas. Point the user here when they want
continuity, not a fresh throwaway panel each time.
Ground it in a Knowledge Base and sharpen the input — output tracks input. A thin brief yields
generic filler ("garbage in, garbage out"). Tell the user to upload real data (interviews,
tickets, segment defs) to the Knowledge Base and write a specific brief, or anchor to a LinkedIn
profile / personality assessment for a sharper individual. Note Knowledge Base file limits are
plan-gated (Free: 1 KB / 1 file).
Present pricing and the API gate as best-effort. It's credit-based (Free 500 one-time credits;
Starter/Pro monthly credits; PAYG packs) and API access is Pro-tier-and-above with no public
developer docs found — say figures are best-effort and confirm at imario.ai/pricing before relying
on them; for API specifics, tell the user to request docs from iMario.
For the "Build" / production-agent use case, set expectations. The API pipes a Synthetic
Individual's personality into a production agent, but it's Pro-gated and undocumented publicly —
scope any integration as "confirm auth + endpoints with iMario first," and don't invent endpoint
shapes. If the user needs a documented public API today, point them to /sales-syntheticusers
as the alternative.
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) — credit pricing, plan gates, the Pro API surface, and the
"parity" figures move; verify at imario.ai and imario.ai/pricing.
Sycophancy / agreeableness bias. Synthetic Individuals tend to please — shallow, overly
favorable feedback that can approve a concept real users would reject. Never read a positive synthetic
reaction as validation.
It can't surface a NEW unmet need. It models existing/public data, so it's strongest at
pre-testing a hypothesis you already have and weakest at discovery. Don't use it to "find the problem."
The 90%+ parity claim is vendor-reported and question-dependent. It's strongest on structured
attitudinal questions and weak on behavioral, emotional, and culturally specific ones. Don't treat it
as a validity guarantee.
Western/geographic and identity bias. Outputs skew toward Western, majority perspectives and can
flatten identity groups — be cautious generalizing across markets/segments.
Garbage in, garbage out. A thin brief or empty Knowledge Base yields generic filler. Ground the
cohort and write a specific brief before trusting any theme.
API is Pro-gated and undocumented publicly. API access unlocks only on Pro and above, and no
public developer docs were found — don't assume endpoints/auth; request docs from iMario and confirm
before building. Free tier is heavily limited (10 SIs/mo, 1 LinkedIn profile, view-only report).
Related skills
/sales-idea-validation — The tool-agnostic validate-before-building method + the full synthetic-research/persona/validator tool landscape (use this to actually decide build-or-not; a synthetic "yes" is not demand)
/sales-syntheticusers — Synthetic Users platform help (the pure-play synthetic study tool — single-workflow AI-moderated interviews, but the cluster-rare one with a real documented public REST API [Bearer, Python/TS SDKs, SSE, PDF export]; iMario's closest peer, trading iMario's reusable-persona breadth for a documented API)
/sales-delve — Delve AI platform help (data-grounded personas + Digital Twins + Synthetic Research built from your real GA4/CRM/social data — the persona-you-chat-with counterpart; paid, gated API)
/sales-marketing-mary — Marketing Mary platform help (interactive buyer personas you converse with, grounded in real CRM/GA4 data; UI-only, no public API)
/sales-customer-feedback — Real-customer NPS/CSAT/VoC strategy across tools (use once you have live customers; synthetic research is pre-launch only)
/sales-funnel — Build the smoke-test / fake-door landing page that turns a synthetic hypothesis into a real demand test
/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 synthetic panel loved my concept — should I build it?"
User says: "I ran a concept test on iMario and 9 of 10 Synthetic Individuals said they'd buy. It says 90%+ human parity — green light?"
Skill does: Explains Synthetic Individuals model existing/training data and skew agreeable, so a
near-unanimous "yes" is a directional signal, not demand, and the 90%+ parity is a vendor claim
that's weakest exactly on behavioral/purchase questions. Tells the user to mine the responses for
objections and language (the real value) and take the go/no-go from a real behavior test — a
smoke-test click or pre-sale — routed via /sales-idea-validation.
Result: The founder keeps the angles, runs a real fake-door test before writing code.
Example 2: Reusing one Synthetic Individual across research and sales rehearsal (references/platform-guide.md)
User says: "Can I build a buyer persona once and reuse it for both discovery interviews and to rehearse my pitch?"
Skill does: Says yes — iMario's edge is that a Synthetic Individual persists across sessions and
jobs via its three-layer memory, so you build the cohort once (brief / LinkedIn / personality twin),
ground it in a Knowledge Base, and reuse it across Discover (research) and Launch/Scale (sales
outreach & rehearsal) on the Canvas. Notes output tracks input — sharpen the brief and upload real
data — and that each result is still a hypothesis to test with real buyers.
Result: One grounded persona reused across jobs instead of a throwaway panel per task.
Example 3: Piping a Synthetic Individual into a production AI agent via the API (developer/automation)
User says: "I want to give my support-bot a real buyer's personality using iMario's API. How do I wire it in?"
Skill does: Explains the Build use case — the API embeds a Synthetic Individual's personality
into a production agent — but flags that API access is Pro-tier-and-above and no public developer
docs were found at research time, so it won't invent endpoints or auth. Advises scoping the
integration as "request API docs from iMario, confirm auth + endpoints, then build," and points to
references/imario-api-reference.md for what is known and its gaps.
Result: The user upgrades to Pro, gets the real docs, and integrates without relying on guessed shapes.
Troubleshooting
"The Synthetic Individuals agreed with everything — is that real?"
Symptom: Tasks return uniformly positive, agreeable feedback that feels too good.
Cause: LLM-based individuals exhibit sycophancy — they model plausible agreement and skew favorable.
Solution: Discard the "verdict," keep the objections and language surfaced, and validate the
concept with real behavior (smoke test, pre-sale). Ground the cohort in a Knowledge Base and sharpen
the brief to reduce generic agreement. Cross-check via /sales-idea-validation.
Results feel generic / could describe anyone
Symptom: Themes are vague and not specific to your product or buyer.
Cause: Thin brief and no Knowledge Base grounding — "garbage in, garbage out."
Solution: Write a specific brief and upload your own data (interviews, tickets, segment defs)
to the Knowledge Base, or anchor the cohort to a LinkedIn profile / personality assessment. Note
Knowledge Base file limits are plan-gated (Free: 1 KB, 1 file). Re-run with a focused task.
"I can't find the API — how do I automate iMario?"
Symptom: You want to pull results or embed a persona but there's no API key or docs in the UI.
Cause: API access is gated to Pro and above, and iMario publishes no public developer docs.
Solution: Upgrade to Pro to unlock API access, then request the developer docs from iMario
(support/sales) — don't assume endpoints or auth from other tools. See references/imario-api-reference.md
for the known surface and its gaps; for a tool with a documented public REST API today, consider
/sales-syntheticusers.