{
  "name": "research-ops-skills",
  "description": "4 Research-Operations skills + 1 orchestrator: clinical-research (study design: protocol synopsis, endpoint selection, sample-size/power, phase-gating, feasibility), research-finance (R&D program budgeting, burn/runway, F&A indirect-rate modeling, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM both-methods, survey/sampling design, segmentation, CI synthesis), product-research (interview/JTBD/usability/concept-test design, saturation, insight repository synthesis). Orchestrator skill uses context: fork. Each sub-skill ships per-skill onboarding (onboard.py), a customization loader (config_loader.py) consumed by every tool, and an isolated opt-in autoresearch evaluator (ar_evaluator.py) bridging to engineering/autoresearch-agent. 24 stdlib-only Python tools (12 analysis + 12 onboarding/customization/autoresearch), 12 reference docs. Distinct from ra-qm-team (regulatory/QM submission), finance (corporate close/valuation), research/grants (NIH funding discovery), product-team (persona/journey/live experiments), marketing-skill (campaign analytics).",
  "version": "2.9.0",
  "author": {
    "name": "Alireza Rezvani",
    "url": "https://alirezarezvani.com"
  },
  "homepage": "https://github.com/alirezarezvani/claude-skills/tree/main/research-ops",
  "repository": "https://github.com/alirezarezvani/claude-skills",
  "license": "MIT",
  "skills": [
    "./skills/research-ops-skills",
    "./skills/clinical-research",
    "./skills/research-finance",
    "./skills/market-research",
    "./skills/product-research"
  ]
}
