alirezarezvani--claude-skills/research-ops/CLAUDE.md

Research Operations — Domain Guide

This file provides domain-specific guidance for skills in research-ops/.

Purpose

The Research Operations domain ships skills that help R&D leads, clinical study teams, R&D finance/controllers, market-research analysts, and product-research / ResearchOps teams plan, fund, scope, and synthesize research across enterprise workstreams. This is the enterprise / cross-functional counterpart to the academic research/ domain (litreview, grants, patent, syllabus, pulse, dossier, notebooklm).

It is not regulatory submission (ra-qm-team), not corporate financial close/valuation (finance/financial-analysis), not funding discovery (research/grants), not persona/journey/live-experiment design (product-team), and not campaign analytics (marketing-skill).

Skills (v2.9.0)

Skill	Purpose	context: fork?
research-ops-skills	Domain orchestrator — routes to 4 sub-skills	YES
clinical-research	Study design: protocol synopsis + endpoint selection + sample-size/power + phase-gating	NO
research-finance	R&D program budgeting + burn/runway + F&A rate modeling + capitalize-vs-expense routing	NO
market-research	TAM/SAM/SOM (both methods) + survey/sampling design + segmentation + CI synthesis	NO
product-research	Study design + saturation/sample method + insight repository synthesis	NO

Hard rules (domain-specific)

1. clinical-research: outputs are study-design RECOMMENDATIONS signed by a named clinician/biostatistician/regulatory owner. Power/sample-size is an ESTIMATE with stated assumptions — never presented as clinical fact. Every tool prints an "ESTIMATE — confirm with a biostatistician" banner.
2. research-finance: every budget output surfaces its assumptions block. Capitalize-vs-expense routes to a NAMED finance owner and never auto-decides accounting treatment.
3. market-research: TAM/SAM/SOM always shows method (top-down AND bottoms-up) + assumptions. Never a single unsourced number.
4. product-research: never fabricates user insight. Sample-size/saturation guidance is method-based and surfaces confidence; single-source claims are flagged as anecdotes, not insights.
5. Stdlib-only Python. Deterministic logic, no LLM calls in scripts.
6. Industry tuning via --profile on every scoring tool.
7. Matt Pocock grill discipline — /cs:grill-research-ops interrogates the plan against the research canon (ICH E9, IAS 38, Cochran, Nielsen, Kotler) before any sub-skill runs.
8. Onboarding-first + customization-in-use. Each sub-skill ships scripts/onboard.py (its own question set) + scripts/config_loader.py. Answers persist to ~/.config/research-ops/<skill>.json (global) or ./.research-ops/<skill>.json (project) and are consumed by every tool (CLI flags override; RESEARCH_OPS_NO_CONFIG=1 bypasses). Customization must change behavior, not sit as decoration.
9. Autoresearch is opt-in + isolated. Each sub-skill ships scripts/ar_evaluator.py — a per-skill, locked ground-truth bridge to engineering/autoresearch-agent. A loop is invoked ONLY on explicit user request and only edits the skill's input file, never the evaluator. No cross-skill coupling.

Build pattern

Path-B contract per skill: SKILL.md + 3 stdlib scoring scripts + 3 references (each citing 5-7 sources) + 1 asset template, plus 3 integration scripts — onboard.py (questionnaire), config_loader.py (customization loader, project→global→defaults precedence), and ar_evaluator.py (isolated autoresearch bridge). SKILL.md includes a "Forcing-question library" section (cited-canon grilling, one question at a time) and the "Onboarding & customization" + "Optimize with autoresearch (opt-in)" sections.

Agent + command pattern

• cs-research-ops-orchestrator — evidence-first R&D operations lead. Voice: "What decision does this research drive, and what's your confidence — show me the method and the assumptions before the number."
• /cs:research-ops <inquiry> — top-level router
• /cs:grill-research-ops <plan> — Matt-style grilling first
• /cs:clinical-research, /cs:research-finance, /cs:market-research, /cs:product-research — direct per-skill invocation

Anti-patterns (domain-level)

• ❌ Skills that overlap ra-qm-team (regulatory/QM submission) — clinical-research designs the study, not the submission
• ❌ Skills that overlap finance/financial-analysis (close/valuation) — research-finance manages R&D program spend
• ❌ Skills that overlap research/grants (funding discovery) — research-finance manages money already won
• ❌ Skills that overlap product-team (persona/journey/live experiments) — product-research is method + repository discipline
• ❌ Skills that overlap marketing-skill (campaign analytics) — market-research is upstream methodology
• ❌ A market size stated as a single unsourced number
• ❌ A clinical power/endpoint output presented as fact rather than an estimate with a named owner
• ❌ A product insight asserted from a single participant

References

• Master plan: documentation/implementation/research-ops-expansion-plan.md
• Matt Pocock derivation: engineering/grill-with-docs
• Academic counterpart: research/ (litreview, grants, patent)
• Regulatory complement: ra-qm-team
• Corporate-finance complement: finance/financial-analysis
• Product complement: product-team