Use when developing or testing the MiMoCode repository and you need to programmatically drive another MiMoCode (mimo) process. Supports headless mimo run with JSON events and interactive TUI via tmux for behavior, integration, and visual regression testing. Covers an installed mimo binary or a dev build launched from…
Use this skill whenever the user wants to find, read, cite, track, download, or analyze academic papers on arXiv. That includes: searching papers by topic, author, category, or arXiv ID; fetching abstracts or full metadata; generating BibTeX citations; downloading PDFs; listing the latest submissions in a field (e.g.…
Operate Claude Code CLI (v2.1+) via the terminal only when the user explicitly requests Claude Code or names this skill. Covers print mode (-p), interactive tmux sessions, and background (--bg) orchestration.
Run, configure, and troubleshoot OpenAI Codex CLI in non-interactive headless environments. Use for Codex automation in Bash or PowerShell, native Windows or WSL2, shell scripts, CI/CD, Docker, Kubernetes, remote servers, agent harnesses, or batch jobs; for constructing codex exec commands; selecting sandbox and…
Use for multi-step feature work, bug fixes, or refactors where requirements need to settle, a feature document should carry design + tasks + delivery evidence, and the change deserves independent review before merge. Use it only when the user explicitly requests this workflow, whether with /compose-next, by name, or…
Use this skill for quantitative product or business analysis: data quality checks, metric diagnostics, KPI design and reporting, dashboards, analytical reports, charts, notebooks, market sizing, semantic layers, and evidence-backed recommendations. Also use it whenever Data Analytics is explicitly invoked.
Assess whether structured data, query results, dashboards, or analytical evidence are trustworthy enough to use. Use when the task is to check data quality, reconcile conflicting sources or metric definitions, or decide whether evidence is safe to cite.
Build a durable analytical report with an answer-first narrative, evidence-backed findings, charts or tables, caveats, recommendations, and source context.
Narrow conversion skill. Invoke only when the user explicitly asks to convert an existing local or blob-hosted HTML analytics report into a Google Doc, DOCX, or shareable document.
Narrow conversion skill. Invoke only when the user explicitly asks to convert an existing Data Analytics report, dashboard, or inline chart export into a PDF artifact.
Create, update, inspect, or repair Data Analytics semantic layers. Use when the user asks to save data context or create a semantic layer that future Data Analytics work can inspect and cite.
Design KPI frameworks, metric definitions, targets, guardrails, and measurement plans for product or business decisions. Use when success metrics, drivers, guardrails, targets, or the measurement approach need to be defined or improved.
Gather business context from connected or provided sources so downstream analysis starts with the right framing. Use when an analytical question depends on missing context, such as what a metric means, what changed recently, or which sources should be checked. If the same prompt asks for diagnosis, recommendation, or…
Route broad Data Analytics requests to the appropriate quantitative analysis, visualization, dashboard, report, notebook, KPI, market-sizing, validation, or semantic-layer workflow.
Create, edit, or validate reproducible SQL or Python notebooks. Use for notebooks, SQL/Python scratchpads, reproducible exploration, audit trails, or runnable companions where the analysis should be reviewable or rerunnable.
Prepare KPI readouts, scorecards, WBR/MBR/QBR updates, and executive summaries from quantitative business or product metrics; use when the task is to report status, compare against targets, explain validated drivers, and state operating implications.
Estimate market, segment, or opportunity size with transparent assumptions and uncertainty. Use for TAM/SAM/SOM, sizing scenarios, or comparing the scale of possible opportunities.
Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy.
Analyze product or business data to support a decision or recommendation. Use when a decision depends on metric-backed evidence, such as choosing a direction, prioritizing an opportunity, evaluating a change, segmenting users, sizing tradeoffs, or deciding what to do next.