research-ops-skills

{
  "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"
  ],
  "source": {
    "spec": "documentation/implementation/research-ops-expansion-plan.md",
    "build_pattern": "Path B (direct conversion) — orchestrator skill uses context: fork. Single domain plugin (commercial/ + business-operations/ pattern), NOT the research/ parent-of-plugins pattern. Every SKILL.md ships a Forcing-question library section per Matt Pocock grill-with-docs discipline. Each sub-skill also ships onboard.py + config_loader.py (customization consumed by every tool, project>global>defaults precedence) and an isolated opt-in ar_evaluator.py that bridges to engineering/autoresearch-agent (loop edits the skill's input file; evaluator is locked ground truth).",
    "distinct_from": "ra-qm-team (ISO 13485/14971, EU MDR, FDA 510(k)/PMA/De Novo/QSR submission — clinical-research designs the prospective study, not the submission). finance/financial-analysis (DCF, ratio analysis, close + report — research-finance manages internal R&D program spend). research/grants (NIH funding DISCOVERY + positioning — research-finance manages money already won). product-team/ux-researcher-designer + product-discovery + experiment-designer (persona/journey artifacts, discovery sprints, live A/B — product-research is method + repository discipline). marketing-skill/campaign-analytics + marketing-demand-acquisition (attribution/ROAS/demand-gen — market-research is upstream methodology)."
  }
}