The skills on this page are parked while we test them. Today, copy a play into your coding agent, or connect the MCP so it can look plays up.
Connect the MCPThree skills run in the coding agent you already use. Each reads what the last one wrote, asks you only what it can’t find, and pulls researched plays from Motifs on the way.
It’s more than what you say at launch. It’s what you choose to build,
how it feels to use, and why someone comes back.
Claude, use Motifs to plan a habit app for language learners, then find a growth play that fits. Start with Planning Head: ask about my idea and write PRODUCT.md.
“Tell me what you want to build, who you imagine using it, and what you want it to help them accomplish.”
Then one to three at a timeDrafts what the code says, then asks only about the gaps. Motifs never sees the code.
Example output. Pick either plan card to switch. The product and its answers are illustrative; every play named is a real record.
Nothing lives in a chat that scrolls away. Every decision lands in a markdown file in your project,
so the agent that builds knows what the agent that planned agreed with you.
Start with one rough sentence, or point your agent at the repo. The Planning Head turns either into a product brief, PRODUCT.md: five sections, and each decision marked by who made it.
What would make someone switch to it?
The Execution Head reads your product brief before anything else. If the direction isn’t settled, it goes back and plans with you first, keeping whatever you already agreed.
Hand it one play or several. The GTM Head weighs each against the same goal: the outcome evidence, whether it transfers to you, and what your build supports. Then it picks, and says how sure it is.
Each head reaches into the same library. A finding never travels without its limits,
and every row says how strong its evidence is.
Motifs gets the search, never your code.
search_plays funnel_stage: retention · min_evidence: controlled_experiment→ summaries, strongest evidence firstget_play comeback-after-miss-or-lapse→ the whole record: mechanism, sources, evidence, when to avoid itA 125-point bonus (about $0.09) for the planned gym visit after a missed one added 0.40 weekly visits over four weeks — 27% above the placebo group's 1.48. Milkman et al. megastudy, 24 Hour Fitness members.
The only outcome evidence is one megastudy of gym members over four weeks, with bonuses worth $0.09 and $0.16. The authors say top-performing estimates are probably inflated and need replication.
The rules the three heads keep, whoever asks.
No made-up studies, statistics or customer evidence. A number keeps its population and its caveat.
What it infers from your repo stays Provisional until you confirm it.
Plays adapt to your product. Your product brief changes only with your agreement.
The biggest result or best-known name doesn’t rank first by default.
Unreleased or partial features are never promised as available.
A plan authorises nothing. It acts only on what you explicitly ask.
Copy it into the agent you already use. No account needed to browse.
A short way back after a gap, with a small bonus for returning
A small bonus for the next planned session after a miss
Review sessions, not gym visits. Streak points, not cash
A higher reward on every session
The only outcome evidence is one megastudy of gym members over four weeks, with bonuses worth $0.09 and $0.16. The authors say top-performing estimates are probably inflated and need replication.
Peer-reviewed work, or a controlled experiment, that tests this mechanism directly.
Credible research on an adjacent question, or a result that is correlational rather than causal.
The company’s own published numbers. Not independently verified, and they chose what to publish.
Untested: a mechanism we find plausible, or one person’s account of what happened to them. Nothing controlled behind it.