القائمة
Synthesize a batch of customer interviews into evidence-for + evidence-against the hypothesis, with pattern surfacing and bias flagging.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Slice a goal into the smallest feature slices that can each be PROVEN — every slice ships with a named eval and an end-to-end test, and a slice you can't evaluate or test doesn't get selected. Use after the goal is set and before the spec, so only provable features make the build.
Guided, stateful provisioning of a product's production stack — deep-links, key-format validation, a secrets backend (fnox recommended, or user-touched .env.local), a resumable ledger, CLI automation after signup, and a blocking A1–A10 live gate. Hands off to /security-check → /ship. The walked version of SETUP.md.
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.
Launch the factory's control plane — scaffold and fill FACTORY-ORDERS (weekly mandate + hard budget), STANDING-ORDERS (autonomous-program authority), HEARTBEAT (weekly pulse), and write lifecycle gates for every registered product. A deliberate one-time ritual (re-run to audit); invoke as /factory-launch, not auto-triggered.
One-shot a new product — folders, Next.js starter, product.config.json, CLAUDE.md, scope.md, PRD skeleton, SETUP.md checklist. The Lovable-like ignition.
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
| name | interview-synthesizer |
| description | Synthesize a batch of customer interviews into evidence-for + evidence-against the hypothesis, with pattern surfacing and bias flagging. |
| model_tier | sonnet |
User has notes from 5+ interviews and asks: "synthesize these", "what did I learn from these calls?", "are we seeing PMF signals?"
Saved to products/<name>/interviews/synthesis-<date>.md:
## Synthesis — interviews <date range> (N conversations)
### Evidence FOR the hypothesis
- <quote from interview> — (P3 — Sarah, Senior PM)
- <quote> — (P5 — ...)
- ...
### Evidence AGAINST the hypothesis
- <quote> — (P2)
- <quote> — (P7)
- ...
### Surprises (what we didn't expect)
- <observation> — surfaced by P4, P6
- ...
### Patterns
- N of N interviewees mentioned <specific behavior / phrase>
- <segmentation pattern>: <subgroup> behaves differently from <other subgroup>
### The strongest single quote
> "<verbatim>" — Person, Role
### Bias check
Compare lists:
- Evidence FOR: <count>
- Evidence AGAINST: <count>
- Ratio: <FOR/AGAINST>
- If FOR >> AGAINST, ask: is this real, or are we hearing what we want? Specifically: did our questions lead the witness? Did we ignore disconfirming signals?
### Recommendation
- CONTINUE: validation pattern is strong — refine and run 5 more
- PIVOT: the right problem nearby is <X>; rerun discovery
- KILL: evidence against is overwhelming — log learnings, move on
- INCONCLUSIVE: too noisy — change target profile or sharpen hypothesis
products/<name>/interviews/raw/).Per factory/playbooks/mvp-stage/agent-handoff-contracts.md:
products/<name>/interviews/raw/ or user-passed paths), each attributable to a distinct person matching the discovery plan's target profile.products/<name>/interviews/synthesis-<date>.md in the exact format above.factory/playbooks/idea-stage/mom-test.mdfactory/playbooks/ai-native-2026/founders-playbook-distilled.md (re: bias check)