research-ops-skills
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns
Profile →npx skills add alirezarezvani/claude-skills --skill research-ops-skills --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Research Operations — Domain Orchestrator The Research Operations surface is **how the enterprise plans, funds, scopes, and synthesizes research** across four workstreams: clinical R&D, R&D finance, market research, and product research. This orchestrator forks its context, routes your inquiry to one of four sub-skills, then returns a digest. Heavy intake (protocol drafts, program ledgers, survey exports, interview transcripts) stays in the forked context. This is the enterprise counterpart to the academic `research/` domain. If your question is about **finding** literature, grants, or patents, use `research/`. If it is about **planning, funding, scoping, or synthesizing** research as an operational discipline, you are in the right place. ## When to invoke | Symptom | Sub-skill | |---|---| | "We're designing a Phase 2 trial — what's the endpoint and sample size?" | `clinical-research` | | "What's our R&D program burn, and is this cost CapEx or OpEx?" | `research-finance` | | "What's the TAM for this product, and how do we survey the segment?" | `market-research` | | "How many users do we interview, and how do we synthesize the findings?" | `product-research` | ## Routing logic (d
- When to invoke
- Routing logic (deterministic)
- Signal table
- Workflow (Matt Pocock grill discipline)
- Step 1 — Explore before asking
- Step 2 — If still ambiguous, ONE forcing question with a recommended answer
- Step 3 — Decision-tree walk for multi-lane inquiries
- Step 4 — Invoke sub-skill in forked context
- Step 5 — Return digest with cited canon challenge
- Forcing-question library (grill-with-docs pattern)
- Onboarding-first (per sub-skill)
- Autoresearch handoff (isolated, opt-in)
- Assumptions
- Non-goals
python3 skills/<sub-skill>/scripts/onboard.py # interactive Q&A python3 skills/<sub-skill>/scripts/onboard.py --show # questions + current config
What does the research-ops-skills skill do?
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill research-ops-skills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.