Detalle del Skill

product-skills

PM domain orchestrator covering major product workstreams.

CoincidenciaDirectaRevisado para gerentes de producto
Fuentealirezarezvani/claude-skillsFuente externa
Instalaciones reportadasNo reportadoSolo señal de popularidad

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Vista previa guardada

SKILL.md

Este extracto es una copia guardada durante la revisión. La fuente externa contiene la versión completa y actual.

---
name: "product-skills"
description: "Use when coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a continuous-discovery loop (Torres cadence tracker + OST linter as machine gates) or a full goal→plan→execute→verify→close run through the repo-wide agent-harness. Distinct from project-management (how to deliver vs what to build), marketing/landing (from-scratch pages), and engineering/agent-harness (the generic loop engine this orchestrator plugs into)."
context: fork
version: 2.11.1
author: Alireza Rezvani
license: MIT
tags: [product, product-management, orchestrator, discovery, ux, analytics, agent-harness]
compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---

# Product Team — Domain Orchestrator & Discovery Loop

This orchestrator does two jobs. **Routing:** fork context, classify a product inquiry
with `scripts/product_goal_router.py` across all 16 product-team lanes (12 bundled + 4
standalone plugins), run exactly one, return a digest. **Looping:** run product work as
bounded agentic loops with machine-checkable gates — the continuous-discovery loop
(weekly cadence scored by `discovery_cadence_tracker.py`, tree structure enforced by
`ost_linter.py`) and goal-scale runs through the repo-wide agent-harness.

## When to invoke

| Symptom | Sub-skill |
|---|---|
| "Prioritize features / RICE / PRD" | `product-manager-toolkit` |
| "OKRs, strategy cascade" | `product-strategist` |
| "Personas, usability, research synthesis" | `ux-researcher-designer` |
| "Design tokens, WCAG contrast" | `ui-design-system` |
| "Competitor matrix, teardown" | `competitive-teardown` |
| "Retention, cohorts, funnels, KPIs" | `product-analytics` |
| "A/B test, sample size, hypothesis" | `experiment-designer` |
| "Discovery, assumptions, opportunity trees" | `product-discovery` |
| "Roadmap comms, release notes, changelog" | `roadmap-communicator` |
| "Spec → runnable repo" | `spec-to-repo` |
| "Landing page (Next.js/Tailwind)" | `landing-page-generator` |
| "SaaS boilerplate" | `saas-scaffolder` |
| "User stories, sprint capacity" | `agile-product-owner` (standalone) |
| "Apple HIG audit" | `apple-hig-expert` (standalone) |
| "PRD from an existing codebase" | `code-to-prd` (standalone) |
| "Summarize papers/articles" | `research-summarizer` (standalone) |

## Routing logic (deterministic)

```bash
python3 scripts/product_goal_router.py --text "<the goal>" --output json
```

Exit 0 → `route_to` names the skill (with `skill_path`, including the standalone
plugins): load its SKILL.md and follow its workflow. Exit 2 → ask ONE clarifying question
naming the listed candidates, with a recommended answer. Exit 3 → no signal: ask the user
to restate the goal with the deliverable named. Never guess silently; never silently
chain — digest first, confirm, then chain.

## The discovery loop (the domain's recurring agentic loop)

Modern discovery is a weekly habit, not a project phase (Torres). Run it as a bounded
loop with two machine gates:

1. **Observe** — maintain `discovery_log.json` (interviews, assumption tests; shape in
   `assets/sample_discovery_log.json`) and score the cadence:
   ```bash
   python3 scripts/discovery_cadence_tracker.py --input discovery_log.json
   ```
   Refuses on < 2 interviews (exit 5) — there is no cadence to measure yet. Output:
   health 0–100, verdict HEALTHY/AT-RISK/DORMANT, named gaps, and `next_loop_action`.
2. **Choose** — the tracker's `next_loop_action` IS the choice:
Leer la fuente completa en GitHub (abre una página externa)
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