LEANSpark (leanspark.ai) platform help — an AI startup-validation system by Ash Maurya, creator of the Lean Canvas, built on Lean Canvas + Continuous-Innovation PDCA cycles, not a one-shot score: a free Lean Canvas builder stress-tested across seven dimensions, persistent memory, a Contradiction Detection engine that flags where plan and evidence stop agreeing, and two-week Plan-Do-Check-Act cycles ending in a Persevere / Pivot / Pause call. Exposes an OAuth MCP server (leanspark.ai/mcp) that reads your validated canvas, positioning, and voice profile into Claude Code or Cursor. Use when building or stress-testing a Lean Canvas, acting on a flagged plan-vs-evidence contradiction, deciding persevere/pivot/pause, setting up the MCP server, weighing free tier vs a paid credits plan, or asking whether it has a REST API. Credit-metered; no REST API. Do NOT use for comparing idea validators or the validate-before-building method (use /sales-idea-validation), or the smoke-test landing page (use /sales-funnel).
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.
LEANSpark (leanspark.ai) platform help — an AI startup-validation system by Ash Maurya, creator of the Lean Canvas, built on Lean Canvas + Continuous-Innovation PDCA cycles, not a one-shot score: a free Lean Canvas builder stress-tested across seven dimensions, persistent memory, a Contradiction Detection engine that flags where plan and evidence stop agreeing, and two-week Plan-Do-Check-Act cycles ending in a Persevere / Pivot / Pause call. Exposes an OAuth MCP server (leanspark.ai/mcp) that reads your validated canvas, positioning, and voice profile into Claude Code or Cursor. Use when building or stress-testing a Lean Canvas, acting on a flagged plan-vs-evidence contradiction, deciding persevere/pivot/pause, setting up the MCP server, weighing free tier vs a paid credits plan, or asking whether it has a REST API. Credit-metered; no REST API. Do NOT use for comparing idea validators or the validate-before-building method (use /sales-idea-validation), or the smoke-test landing page (use /sales-funnel).
argument-hint
[describe what you need help with in LEANSpark]
license
MIT
version
1.0.0
tags
["sales","idea-validation","platform"]
LEANSpark Platform Help
LEANSpark (leanspark.ai) is "the decision layer for founders" — an AI startup-validation system
by Ash Maurya (creator of the Lean Canvas, author of Running Lean), built on his Lean Canvas +
Continuous-Innovation framework. Unlike the one-shot "score my idea" validators, it keeps persistent
memory of your model, interviews, and experiments, runs two-week Plan-Do-Check-Act cycles over
~90 days, and has a Contradiction Detection engine that flags where your plan and your evidence stop
agreeing — ending each sprint in a Persevere / Pivot / Pause decision. It also exposes an OAuth
MCP server so Claude Code / Cursor can read your validated model.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
Ask only what you can't infer from the user's prompt:
Where are you? (a) building/stress-testing a Lean Canvas, (b) staring at a seven-dimension result
or a flagged contradiction and unsure what to do, (c) mid-cycle and deciding persevere/pivot/pause,
(d) wiring the MCP server into Claude Code / Cursor, (e) weighing free tier vs a paid credits plan,
(f) asking whether it has a REST API / how to get data out.
What's the idea, in one sentence? (helps interpret the canvas and the seven-dimension stress test).
What evidence have you got so far — a hunch, customer interviews, an experiment result, a landing
page, a waitlist, or someone offered to pay?
Skip-ahead rule: if the user's prompt already contains enough context, skip to Step 2.
Step 2 — Route or answer directly
LEANSpark is one validation system. Much of the thinking a founder needs is tool-agnostic — route it:
The user's real question
Route to
Should I trust this? How do I actually validate? The evidence ladder, comparing validators
/sales-idea-validation
Build the smoke-test / fake-door landing page the demand test runs on
/sales-funnel
Grow a pre-launch waitlist and capture signups
/sales-audience-growth
Run the ~10 customer interviews that feed the evidence side
/sales-idea-validation
Reddit-based real-demand signal to cross-check the model
/sales-trendseeker
When routing, give the exact command: "This is a validation-method question — run: /sales-idea-validation {the user's original question}"
Answer directly only for LEANSpark-specific mechanics (the 12-block canvas, the seven dimensions,
the contradiction engine, PDCA cycles, persevere/pivot/pause, credits & modes, the MCP server).
Step 3 — LEANSpark platform reference
Read references/platform-guide.md for the full reference — the 12-block canvas and seven-dimension
stress test, the persistent-memory / contradiction-detection / PDCA loop, credits & the Reactive /
Attentive / Proactive modes, pricing/plan gates, the MCP server (setup, scopes, the one write-back tool),
and how to get data out. Read references/leanspark-api-reference.md for the MCP surface verbatim.
Answer using only the relevant section — don't dump the whole guide.
Step 4 — Actionable guidance
The canvas, seven-dimension score, and contradiction flags are coaching over your inputs — not demand.
LEANSpark's edge over pure-LLM validators is that it's built around running real experiments and
interviews and tracking that evidence over 90 days — but a well-organized canvas with no real customer
evidence fed in is still just a plan. Keep the structure and the flagged contradictions; take the
go/no-go from a real behavior test (smoke test / pre-sale). Route that to /sales-funnel + /sales-audience-growth.
The Contradiction Detection engine only checks things you told it — it can't see that your evidence base is imaginary.
It flags where your plan and your logged evidence disagree (e.g. positioning vs. interview feedback),
which is genuinely useful — but "no contradictions" means your inputs are internally consistent, not
that strangers want it. Treat a flagged contradiction as your next thing to go resolve with real customers.
Feed it real evidence, then let it compound. Its whole value proposition is persistent memory —
log actual interviews and experiment results, not guesses. Tell the user the system is only as good as
the evidence they put in; thin or invented inputs yield confident but empty coaching.
Read persevere/pivot/pause as a cycle verdict, not a final grade. Each two-week PDCA cycle ends in
Persevere (evidence supports the current model — keep testing), Pivot (a core assumption failed — change
the model), or Pause (stop/park). It's a checkpoint against pre-set success criteria, so anchor it on
whether the experiment hit its threshold, not on how the AI "feels" about the idea.
Present all pricing as best-effort, and explain credits + modes. Plans are credit-metered (Free
~25 credits/mo, paid tiers up to ~1,600) and pricing may have changed — point to leanspark.ai/pricing.
The "mode" scales with tier: Reactive (you drive) → Attentive (proactive nudges) → Proactive
(daily briefings, autonomous campaigns, background watchers). The free Lean Canvas builder is usable
without a card.
The MCP server is the only programmatic surface — there's no REST API or webhooks. To use LEANSpark
data in Claude Code: claude mcp add --transport http leanspark https://leanspark.ai/mcp, then authorize
via OAuth in the browser and pick which idea to expose. It's read-mostly (validated canvas,
positioning, competitive evidence, voice profile) plus one write-back tool to save deliverables into
your active experiment; each connection is scoped to a single idea and revocable in Settings → MCP.
Don't confuse it with the free five-minute canvas generators or one-shot scorers. LEANSpark is
deliberately a longitudinal 90-day processbuilt by Ash Maurya, the creator of the Lean Canvas
(persistent memory + two-week PDCA cycles + contradiction detection), not a 60-second verdict — and it's
credit-metered (always present its pricing as best-effort and point to leanspark.ai/pricing). When a
user weighs it against a fast/free canvas generator, lead with that longitudinal-vs-one-shot contrast and
the creator-of-the-Lean-Canvas authenticity, note the free Lean Canvas builder needs no card, and point
them to /sales-idea-validation for the full comparison.
If you discover a gotcha, workaround, or tip not covered in references/learnings.md, append it there.
Gotchas
Best-effort from research (2026-07) — the AI-validator tool set churns fast; verify tiers, the modes, credits, and the MCP scopes at leanspark.ai.
A tidy canvas is not validated demand. Even from Ash Maurya, the creator of the Lean Canvas, LEANSpark
coaches and tracks your evidence — it doesn't manufacture demand. Follow every green light with a real-behavior test.
Contradiction detection is bounded by your inputs. It surfaces conflicts between what you logged;
it can't tell you that the whole evidence base is thin or imagined. Garbage in, confident coaching out.
It's a 90-day commitment, not an instant score. The value is the persistent memory + PDCA cadence
over weeks; a founder wanting a one-shot number will find the deliberate pace a mismatch.
Credit-metered with tiered "modes." Free is ~25 credits/mo in Reactive mode; proactive/autonomous
behavior (daily briefings, background watchers) is top-tier only. Confirm current credits/prices at leanspark.ai/pricing.
No REST API or webhooks — MCP only. The automation surface is the OAuth MCP server (read-mostly +
one write-back tool), scoped to one idea. Don't plan a REST integration; there isn't one.
Persevere/Pivot/Pause depends on pre-set success criteria. If you don't define what "success" for a
cycle looks like up front, the verdict drifts toward an AI opinion — set the threshold before the sprint.
Related skills
/sales-idea-validation — the tool-agnostic validate-before-building method and the full idea-validator comparison (start here to decide whether to trust any score or system)
/sales-funnel — build the smoke-test / fake-door landing page the real demand test runs on
/sales-audience-growth — grow a pre-launch waitlist and capture signups once you're testing demand
/sales-trendseeker — Reddit-based real-demand signal to cross-check LEANSpark's model
/sales-juma — the other tool in this cluster with a callable MCP server, if you're comparing MCP surfaces
/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: "LEANSpark flagged a contradiction between my plan and my interviews — now what?"
User says: "The Contradiction Detection thing says my positioning conflicts with my customer feedback. What do I do?"
Skill does: Explains the engine compares what you logged (positioning vs. interview evidence) and that
the flag is your top thing to go resolve with real customers — not a verdict on the idea. Suggests re-running
the affected experiment with a sharper customer/problem, and reminds the user that "no contradiction" only
means internal consistency, not demand — the go/no-go still comes from a smoke test / pre-sale
(/sales-funnel + /sales-audience-growth).
Result: The founder treats the contradiction as a concrete next experiment instead of a pass/fail grade.
Example 2: "Is LEANSpark worth it over a free five-minute lean-canvas generator?"
User says: "I can get a lean canvas in five minutes elsewhere for free — why pay for LEANSpark?"
Skill does: Frames LEANSpark as a longitudinal system (persistent memory + two-week PDCA cycles +
contradiction detection over ~90 days from the Lean Canvas creator), not a one-shot canvas or score — so
its value only shows up if you actually run experiments and log evidence over weeks. Notes the free Lean
Canvas builder is usable without a card, explains credits/modes as best-effort, and points to
/sales-idea-validation to compare it against the fast/free scorers.
Result: The user picks based on whether they'll commit to the process, not the price tag.
Example 3 (automation): "Can I pull my LEANSpark model into Claude Code — is there an API?"
User says: "I want my validated canvas and positioning available in Claude Code / Cursor. Does LEANSpark have an API or webhook?"
Skill does: States there's no REST API or webhooks — the only programmatic surface is the OAuth
MCP server: claude mcp add --transport http leanspark https://leanspark.ai/mcp, then authorize in the
browser and select which idea to expose. Explains it's read-mostly (validated canvas, positioning,
competitive evidence, voice profile) plus one write-back tool to save a deliverable into the active
experiment, scoped to one idea and revocable in Settings → MCP — so you can generate on-brand copy grounded
in the validated model, but you can't script a full data export.
Result: The user connects the MCP server and reads their model into Claude Code instead of hunting for a REST endpoint.
Troubleshooting
The seven-dimension result / coaching feels generic
Symptom: The stress test or the AI's guidance reads bland and could apply to any idea.
Cause: LEANSpark coaches over the evidence you've logged; with only a one-line idea and no real
interviews or experiments in memory, it has nothing specific to reason from.
Solution: Feed it real evidence — log actual customer interviews and experiment results, answer the
canvas blocks concretely (especially early adopters and the problem), and let the persistent memory
compound over a cycle. Then cross-check the model against a real-demand signal (/sales-trendseeker) and
a smoke test.
"I connected the MCP server but can't get my full data out"
Symptom: The MCP tools read the model but there's no bulk export / no REST endpoint.
Cause: LEANSpark is UI + MCP only — the MCP server is read-mostly with a single write-back tool, and
there is no public REST API or webhooks.
Solution: Use the MCP reads for what they're for (grounding content/positioning in Claude Code/Cursor)
and the one write-back tool to save deliverables into your active experiment. For anything the MCP doesn't
expose, copy from the UI. Don't design a pipeline around a REST API that doesn't exist.
Ran out of credits / confused by Reactive vs Proactive
Symptom: The tool stops doing work, or the "mode" behaves differently than expected.
Cause: Plans are credit-metered and the mode is tier-gated — Free (~25 credits/mo) is Reactive
(you initiate); proactive nudges and autonomous/always-on behavior are higher tiers only.
Solution: Confirm current credits and tier behavior at leanspark.ai/pricing. Budget credits for real
work (logging evidence, running cycles) rather than idle chat, and upgrade only if you genuinely want the
Attentive/Proactive daily-coaching behavior — the free Lean Canvas builder needs no card.
