research-ops-skills

Clinical study design. Select and classify endpoints, estimate sample size / power (means / proportions / survival), and score a study plan for a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named clinical owner — never clinical fact. Direct invocation of the clinical-research skill.

Matt Pocock-style docs-anchored grilling for a Research Operations plan — clinical study, R&D budget, market size, or product study. Walks the plan against the research canon (ICH E9, IAS 38, Cochran, Kotler, Nielsen) one question at a time, recommends an answer per question, and refuses to invoke any sub-skill until the lane-defining decisions are locked. Use before running /cs:research-ops on a fuzzy plan.

Market research methodology. Size a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single number), plan a survey sample size with finite-population correction and per-segment minimums, and score candidate segments against Kotler's criteria. Outputs always show method + assumptions. Direct invocation of the market-research skill.

Product / user research methodology. Select the right method for the goal (generative vs evaluative vs validation), compute method-based saturation / sample size with an explicit confidence level, and synthesize coded observations into insights while flagging single-source anecdotes. Never fabricates insight. Direct invocation of the product-research skill.

R&D program finance. Build a multi-period program budget with the F&A (indirect) split, track burn rate and runway against value-inflection milestones, and route R&D cost items to a capitalize-vs-expense determination. Every budget surfaces its assumptions; capex-vs-opex routes to a named finance owner and never auto-decides. Direct invocation of the research-finance skill.

Evidence-first R&D operations lead. Routes enterprise research inquiries (clinical study design / R&D finance / market research / product research) to the right sub-skill via the research-ops-skills orchestrator. Forks context to keep heavy intake (protocol drafts, program ledgers, survey exports, interview transcripts) out of the parent thread. Signature forcing question — "What decision does this research drive, and what's your confidence?"

Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (ISO 13485, EU MDR, FDA 510(k)/PMA/QSR), not the study design.

Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number), planning a survey sample size with finite-population correction and per-segment minimums, or scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria. Outputs always show the method and the assumptions. For market-research analysts and product-marketing at the sizing/survey/segmentation moment. Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — this is the evidence-building methodology, not live-campaign optimization.

Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.

Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).

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 a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).