google-workspace-cli

Snowflake SQL, data pipelines (Dynamic Tables, Streams+Tasks), Cortex AI functions, Snowpark Python, and dbt integration. Includes query helper script, reference guides, and troubleshooting.

Marketplace

End-to-end SLO/SLI/error-budget discipline per Google SRE Workbook. Ships SLO designer (refuses to render without required fields), error-budget calculator with multi-window burn-rate alert thresholds (PromQL-shaped), and SLO reviewer that catches the 7 common bugs. 4 references on principles + SLI design + error budget math + composition with feature-flags-architect/chaos-engineering/kubernetes-operator. Asset templates for SLO YAML and error budget policy. /slo-design slash command. NOT a generic observability skill.

Hypothesis testing, A/B experiment analysis, sample size calculation, and confidence intervals. 3 stdlib-only Python tools: Z-test/t-test/chi-square with effect sizes, sample size calculator with power tradeoffs, and Wilson score confidence intervals.

End-to-end feature-flag discipline: classify, ship, ramp, retire. Detects stale flags as debt, generates phased rollout plans (ring/linear/log/cohort), and audits every flag for a documented kill switch. 3 stdlib Python tools, 4 references on flag taxonomy + provider trade-offs (LaunchDarkly/GrowthBook/Statsig/Unleash/Flipt/DIY) + rollout strategies + lifecycle. /flag-cleanup slash command. Cross-tool compatible.

Production-grade Playwright testing toolkit. 9 skills, 3 agents, 55 templates, TestRail + BrowserStack MCP integrations. Generate tests, fix flaky failures, migrate from Cypress/Selenium.

Autonomous experiment loop — optimize any file by a measurable metric. 5 slash commands (/ar:setup, /ar:run, /ar:loop, /ar:status, /ar:resume), 8 built-in evaluators, configurable loop intervals (10min to monthly).

Enterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork) + clinical-research (study design: protocol synopsis + endpoint selection + sample-size/power for means/proportions/survival + phase-gate feasibility) + research-finance (R&D program budgeting with F&A split + burn/runway + capitalize-vs-expense routing + portfolio ROI) + market-research (TAM/SAM/SOM computed both top-down and bottoms-up + survey sampling with FPC and per-segment minima + Kotler segmentation scoring) + product-research (goal-matched study design + method-based saturation with confidence + insight synthesis that flags single-source anecdotes). Hard rules: clinical outputs are estimates with a named clinical owner (never fact), finance outputs surface assumptions and route capex-vs-opex to a named finance owner (never auto-decide), market sizes show method + assumptions (never a single number), product insights require recurrence across independent participants. Each sub-skill ships per-skill onboarding questions (onboard.py), a customization config consumed by every tool, and an isolated opt-in autoresearch evaluator (ar_evaluator.py) bridging to engineering/autoresearch-agent. 24 stdlib 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 (funding discovery), product-team (persona/journey/live experiments), marketing-skill (campaign analytics).

Compact the current conversation into a handoff document for another agent to pick up. Configurable save location, redaction enforcement, SessionStart auto-load + SessionEnd reminder, self-check fidelity script, --refresh flag, mtime-guarded cleanup. Inspired by Matt Pocock's handoff (MIT).

Patent prior-art + IP landscape skill. FTO/novelty/family-resolver via 3-pass Jaccard heuristic. Research-pack convention. Path-B from megaprompt 12.