Compute statistical power, required sample size, and minimum detectable effect (MDE) for a study design, then write a registry-ready power section. Handles two-arm RCTs (with clustering / ICC and unequal allocation), multiple-arm corrections, and a simulation-based power option for non-standard designs (DiD/event-study, IV, panel). Use when user says "power analysis", "power calculation", "MDE", "minimum detectable effect", "how big a sample do I need", "is my study powered", "power for an RCT", or when /preregister needs a power section for an experiment. Produces a power/MDE table, power curves, and a methods paragraph to paste into a preregistration.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The `power-analysis` skill’s runtime workflow ingests user-provided free text/spec parameters via `--input <spec>` (an `/interview-me` spec under `quality_reports/specs/`) to elicit design parameters, so an outsider can supply that text at invocation time for the LLM to read and use.
9d371f0
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.