Articos (articos.com) platform help — a synthetic-user research tool: AI personas built on 30 Big-Five facets + cognitive-bias mapping run user interviews, concept tests, and A/B tests → a synthesized report (motivations, objections, recommendations) + a Talk-to-Research chat, in ~30 min, no recruiting. Its edge is enforced stance diversity (deliberately generates skeptics, not just fans) and a peer-reviewed 86% accuracy claim — but it's synthetic (an AI opinion), not a real panel. Self-serve: free trial + 2 researches, then Starter/Pro or a one-time Research Pack; UI-only, no API. Use when setting up an Articos study, picking interview vs concept vs A/B mode, describing an audience, reading the report, judging the 86% claim, budgeting researches, exporting without an API, or Articos vs a real panel. Do NOT use for the validate-before-building method or comparing research tools (use /sales-idea-validation), real-panel testing (use /sales-wynter or /sales-pickfu), or synthetic usability (use /sales-uxia).
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.
Articos (articos.com) platform help — a synthetic-user research tool: AI personas built on 30 Big-Five facets + cognitive-bias mapping run user interviews, concept tests, and A/B tests → a synthesized report (motivations, objections, recommendations) + a Talk-to-Research chat, in ~30 min, no recruiting. Its edge is enforced stance diversity (deliberately generates skeptics, not just fans) and a peer-reviewed 86% accuracy claim — but it's synthetic (an AI opinion), not a real panel. Self-serve: free trial + 2 researches, then Starter/Pro or a one-time Research Pack; UI-only, no API. Use when setting up an Articos study, picking interview vs concept vs A/B mode, describing an audience, reading the report, judging the 86% claim, budgeting researches, exporting without an API, or Articos vs a real panel. Do NOT use for the validate-before-building method or comparing research tools (use /sales-idea-validation), real-panel testing (use /sales-wynter or /sales-pickfu), or synthetic usability (use /sales-uxia).
argument-hint
[describe what you need help with in Articos]
license
MIT
version
1.0.0
tags
["sales","market-research","platform"]
Articos Platform Help
Articos (articos.com) is a synthetic-user research tool. You describe a target audience, and Articos
generates AI personas — each built on 30 Big Five personality facets plus cognitive-bias mapping —
then runs one of three modes and synthesizes a research report (motivations, objections, recommendations)
in ~30 minutes, with no recruiting: User Interviews (explore an audience/problem/concept),
Concept Testing (message/value-prop/positioning variants), and A/B Testing (a landing page or two
variants). Plus a "Talk to Research" chat and probing follow-ups; reports are shareable, white-label
on Pro.
Its niche: synthetic, not a real panel — the cheap/fast pre-flight counterpart to real-panel testers
(/sales-wynter B2B, /sales-pickfu consumer) and a peer of the synthetic-study tools (/sales-syntheticusers,
/sales-ditto, /sales-atypica). Two real differentiators: (1) enforced stance diversity — it
deliberately generates skeptics/detractors, not just fans, which mitigates (doesn't cure) the "personas
skew agreeable" bias the whole cluster suffers, and the objections are the highest-signal output; and (2) a
peer-reviewed 86% accuracy claim (46 studies / 9 domains, 86% recall vs expert research, marketed 7.5× over
a bare LLM) — better-sourced than peers' self-reports, but best-effort. Self-serve: free trial + 2
researches, then Starter/Pro or a one-time Research Pack.
The double caveat to say almost every time: (1) a synthetic result is an AI opinion, not real behavior —
even with 30 Big-Five facets and enforced skeptics it carries bias, can't reproduce observed behavior, and
Articos itself says ~70–80% of insights hold up; trust relative comparisons + the objections/rationale
over absolute reads, and validate the winner with real people. (2) Even real resonance is not demand —
take the willingness-to-pay / conversion go/no-go to a real behavior test via /sales-idea-validation.
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 Articos?
A) Set up a study — pick the mode (User Interviews / Concept Testing / A/B Testing) and what
you're testing (audience/problem, message/value-prop, or a landing page/variants)
B) Describe the audience — the buyer/user you want personas matched to
C) Read results — the synthesized report (motivations, objections, recommendations), per-persona
answers, and the Talk-to-Research chat / probing follow-ups
D) Budget — researches per plan, Starter/Pro vs the one-time Research Pack, the free trial
E) Get data out — export/automation (there is no API/webhooks/MCP)
F) Choose — Articos (synthetic) vs a real panel (/sales-wynter / /sales-pickfu) or another
synthetic-study tool (/sales-syntheticusers, /sales-ditto)
Is a decision riding on this, or is it a fast pre-flight? This decides how hard to push the "synthetic
is directional; validate the winner with real people / real behavior" message.
Skip-ahead: if the user wants the validate-before-building method or a cross-tool comparison, 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
The validate-before-building method, or comparing research/validation tools across the market
/sales-idea-validation {question}
A REST API / webhook / MCP-native research pipeline (Articos has none — it's UI-only)
/sales-userintuition {question}
Running a real behavior demand test (smoke-test page, waitlist, pre-sale) after a synthetic study
/sales-idea-validation or /sales-funnel{question}
Real-panel B2B message/positioning testing (verified professionals in your ICP)
/sales-wynter {question}
Real-panel consumer creative/message split-testing (real people vote + explain)
/sales-pickfu {question}
A census-calibrated synthetic panel with a studies API + free tier
/sales-ditto {question}
The pure-play synthetic interview-study tool with a documented REST studies API
/sales-syntheticusers {question}
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer Articos-specific questions using Step 3.
Step 3 — Articos reference
Read references/platform-guide.md for the full reference — the three research modes + the
automation-surface table (everything is UI-only), the persona architecture (30 Big-Five facets, cognitive-bias
mapping, enforced stance diversity), the 86%-accuracy methodology and how to caveat it, best-effort pricing
(Starter/Pro/Research Pack + trial) and plan gates (probing follow-ups, Talk-to-Research queries, white-label),
the Study → Persona → Report data model, how to write a clean audience + variant set, and how to read the
synthesized report + objections (relative, not absolute).
There is no articos-api-reference.md — Articos has no public API/webhooks/MCP (best-effort; confirm
at articos.com). Don't invent endpoints.
Answer using only the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
Lead with the double caveat: synthetic = AI opinion, and resonance ≠ demand. Whatever the user asks,
make explicit that (1) Articos personas are synthetic — an AI opinion, so even a clean report is not
real behavior (the vendor itself says ~70–80% of insights hold up); and (2) even real resonance is
stated preference, not a purchase. Both caveats stack: trust the written objections/rationale and
relative comparisons, validate the winner with real people, and take the willingness-to-pay / conversion
go/no-go to a real behavior test via /sales-idea-validation. Credit the enforced stance diversity
(deliberately generating skeptics) as a genuine bias mitigation — but not a cure that makes synthetic output
real behavior, so still route the decision to real validation.
Frame the 86% accuracy claim honestly. It's peer-reviewed (46 studies / 9 domains, 86% recall vs
expert research, a marketed 7.5× lift over a bare LLM) — a stronger provenance than the cluster's
self-reported claims — but it's still a recall benchmark on past studies, not a guarantee for the user's
audience, and Articos itself caveats ~70–80% hold-up. Present it as best-effort, not proof.
Match the mode to the job, and describe the audience well. Recommend User Interviews for exploring an
audience/problem, Concept Testing for "does my message/value-prop land", and A/B Testing for picking
between landing-page variants — reserving Articos for the fast, cheap synthetic pre-flight (route real-panel
decisions to /sales-wynter / /sales-pickfu, build-or-not to /sales-idea-validation). A vague audience
yields generic personas — describe the buyer specifically, and use probing follow-ups / Talk-to-Research
to interrogate the why.
Treat automation as UI-only, and don't invent endpoints. When any API/webhook/export/integration comes
up, state that Articos has no public REST API, webhooks, Zapier/Make, or MCP server (best-effort — confirm
at articos.com); data-out is manual export/sharing (report link, PDF). Don't design a REST/webhook pipeline
or guess endpoints; if a programmatic pipeline is a hard requirement, route to /sales-userintuition.
Size a run by researches, and call pricing best-effort. Cost is a subscription (Starter ~10/mo; Pro
unlimited + white-label) or a one-time Research Pack (credits, no expiry) — pick by how many studies you'll
run. Present every number as best-effort (point to articos.com/pricing) and note the free 7-day trial (2
researches, no card) for a first run. Running more personas/studies tightens the average — it doesn't turn an
AI opinion into demand.
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) — Articos's pricing (Starter/Pro rates, Research Pack, launch-promo
discounts), research quotas, persona architecture, accuracy methodology, and export options change; verify at
articos.com and articos.com/pricing.
Synthetic ≠ real behavior (enforced skeptics mitigate, don't cure). Personas are an AI opinion; even
with 30 Big-Five facets and deliberately-generated skeptics they inherit bias amplification and can't
reproduce observed behavior — the skeptic design reduces agreeable bias but doesn't upgrade output to demand.
Articos itself says ~70–80% of insights hold up — trust relative comparisons + the objections, validate
the winner with real people.
Resonance ≠ demand. A strong report or a persona "I'd use this" is what lands with a reader-model, not
a purchase. Take the go/no-go to a real behavior test (smoke test, pre-sale) via /sales-idea-validation.
The 86% accuracy figure is a benchmark, not a guarantee. It's peer-reviewed (46 studies / 9 domains,
86% recall vs expert research, 7.5× over a bare LLM) — better-sourced than peers' self-reports — but it's a
recall stat on past studies, not proof it'll match your audience. Present as best-effort.
No public API/webhooks/MCP/Zapier — automation is manual export. Data-out is a report link / PDF export;
don't invent endpoints or design a webhook pipeline (that's a /sales-userintuition job). Best-effort —
confirm at articos.com.
Priced by researches, not personas. Starter is quota-capped (~10/mo), Pro is unlimited + white-label,
and a one-time Research Pack never expires — pick by re-run count. A bigger synthetic run tightens the
average, it doesn't make an AI opinion into demand.
It's synthetic user research, not usability or idea validation. For a built product/prototype use
/sales-uxia (synthetic) or /sales-uxtweak (real); for real-panel message testing use /sales-wynter
(B2B) / /sales-pickfu (consumer); for build-or-not use /sales-idea-validation.
Related skills
/sales-idea-validation — The tool-agnostic validate-before-building method + the full research/validator tool landscape (use to decide build-or-not; a synthetic "yes" is an AI opinion, not demand). Install: npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code
/sales-syntheticusers — Synthetic Users, the pure-play synthetic interview-study peer with a documented public REST studies API — the pick when you need to run synthetic studies programmatically. Install: npx skills add sales-skills/sales --skill sales-syntheticusers -a claude-code
/sales-ditto — Ditto, the census-calibrated synthetic-panel peer with a studies API + free-tier key and Claude Code skills — pick it for census filtering or an API pipeline. Install: npx skills add sales-skills/sales --skill sales-ditto -a claude-code
/sales-societies — Artificial Societies, the network simulator Articos positions against (predicts how a post/message spreads, not isolated reactions) — the self-serve synthetic alternative shoppers compare Articos to. Install: npx skills add sales-skills/sales --skill sales-societies -a claude-code
/sales-wynter — Wynter, the real-panel B2B message-testing counterpart (80k+ LinkedIn-verified professionals in your ICP). Pick Wynter for real B2B positioning signal; Articos for a synthetic pre-flight. Install: npx skills add sales-skills/sales --skill sales-wynter -a claude-code
/sales-pickfu — PickFu, the real-panel consumer counterpart (15M+ real people vote and explain, with a real REST API/MCP/CLI). Pick PickFu for a real-panel decision; Articos for a fast/cheap synthetic pre-flight. Install: npx skills add sales-skills/sales --skill sales-pickfu -a claude-code
/sales-userintuition — The REST-API/webhook/MCP research peer — the pick when you need a programmatic pipeline Articos's UI-only surface can't offer. Install: npx skills add sales-skills/sales --skill sales-userintuition -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: "Articos personas loved my concept and gave strong scores — should I build?"
User says: "I ran a concept test in Articos and the personas were really positive about my SaaS idea, and even the skeptics came around. Green light to build?"
Skill does: Names the double caveat — the personas are synthetic (an AI opinion), not real behavior
(vendor says ~70–80% of insights hold up) and even real resonance is not demand — credits the enforced-skeptic
design as mitigation not a cure, reframes the output as relative signal + objections not a verdict, and routes
the user to validate with real people (/sales-wynter / /sales-pickfu) + a real behavior test via /sales-idea-validation.
Result: The user keeps the objections + winning direction and earns the go/no-go from real behavior, not a synthetic report.
Example 2: "How do I pull Articos results into our data warehouse automatically?" (developer/automation)
User says: "I want a webhook to fire when an Articos study finishes and POST the report into BigQuery. What's the endpoint and how do I authenticate?"
Skill does: States plainly that Articos has no public REST API, webhooks, Zapier/Make, or MCP server
(best-effort — confirm at articos.com), so there's no endpoint or key to build against, and does not
invent one — the only data-out is manual export / a shared report link. Routes an automated
completion-to-warehouse pipeline to /sales-userintuition (API + 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: "Articos or Artificial Societies for a fast pre-launch read?"
User says: "I want a cheap synthetic read on my launch message before I publish. Articos or Societies?"
Skill does: Frames the trade-off — Articos runs studies (interviews / concept / A/B) on bias-diverse
personas → a report with objections; Artificial Societies (/sales-societies) models a network predicting
how a post spreads — a different question. Picks Articos for "what do people think / what objections surface",
Societies for "how far will this post travel"; both are synthetic (AI opinions), so validate the winner with
a real panel and take demand to a real behavior test.
Result: The user picks the synthetic tool that matches the actual question and keeps demand as a separate, real test.
Troubleshooting
"Can I trust the Articos report — how accurate is it?"
Symptom: The user wants to know whether the synthesized report reflects how real people will react.
Cause: Personas are synthetic — LLM models built on 30 Big-Five facets + cognitive-bias mapping with enforced skeptics. The 86% accuracy is a peer-reviewed recall benchmark (46 studies / 9 domains, 7.5× over a bare LLM), stronger than peers' self-reports, but it's a stat on past studies; Articos itself says ~70–80% of insights hold up.
Solution: Read the report as a relative signal + the written objections (the enforced skeptics are the most useful part), not a calibrated verdict. Validate the winner with real people (/sales-wynter / /sales-pickfu) and take the go/no-go to a real behavior test (/sales-idea-validation).
"Where's the Articos API / webhook to export results?"
Symptom: You're looking for an API key and a webhook to fire when a study completes.
Cause: Articos is UI-only — no public REST API, webhooks, Zapier/Make, or MCP server (best-effort; confirm at articos.com). Data-out is manual export / a shared report link.
Solution: Export or share the report from the dashboard. For a programmatic warehouse/CRM pipeline, use an API-native tool — route to /sales-userintuition. Don't build against guessed endpoints.
"Which Articos plan do I need, and is there a way to try it first?"
Symptom: The user wants to budget and de-risk a first run.
Cause: Articos bills by researches — Starter is quota-capped (~10/mo), Pro is unlimited + white-label, and a one-time Research Pack (credits, no expiry) suits occasional use — plus launch-promo discounts that change (best-effort).
Solution: Start with the free 7-day trial (2 researches, no card) to see real output, then pick by re-run count: the one-time pack for a few studies, Starter for steady monthly use, Pro for high volume or white-label. Confirm current rates at articos.com/pricing. More researches tighten the average but don't make a synthetic result into demand.
