Ab Testing

Experiment design, metrics, ethics, and analysis. Use when running product experiments responsibly.

Security Scan

The skill is an instruction-only AB testing workflow whose requested resources and instructions match its stated purpose and carry minimal technical risk.

Purpose & Capability

Name/description matches the SKILL.md content: a structured AB testing workflow. There are no unexpected requirements (no credentials, no binaries) that don't belong to an experiment-design guidance skill.

Instruction Scope

The SKILL.md contains stepwise guidance, checklists, and questions to ask users. It does not instruct the agent to read files, access environment variables, call external endpoints, or perform system operations outside normal conversational behavior.

Install Mechanism

No install spec and no code files — instruction-only. Nothing is downloaded or written to disk, so installation risk is minimal.

Credentials

The skill requests no environment variables, credentials, or config paths. This is proportionate for a guidance/consulting skill.

Persistence & Privilege

always is false and the skill does not request persistent or elevated privileges or modification of other skills/config. Model invocation is permitted (the platform default), which is appropriate for a user-invokable guidance skill.

Assessment

This skill is instruction-only and appears coherent for giving AB testing guidance. Because the source is unknown, consider: (1) you are installing a set of conversational instructions only — it will not install code or ask for credentials; (2) treat any recommendations as advice to be validated against your org's data, metrics, and pipelines before acting; (3) prefer not to paste secrets or sensitive data into the conversation; and (4) if you require an auditable or integrated workflow (automated experiment rollout, telemetry access), prefer a skill explicitly tied to your measurement tooling with documented auth and provenance.

AB Testing Skill

This skill provides structured guidance for AB Testing work. Act as an active guide: confirm triggers, propose the stages below, and adapt if the user wants a lighter pass.

When to Offer This Workflow

Trigger conditions:

• User mentions ab testing or closely related work
• They want a structured workflow rather than ad-hoc tips
• They are preparing a review, rollout, or stakeholder communication

Initial offer: Explain the four stages briefly and ask whether to follow this workflow or work freeform. If they decline, continue in their preferred style.

Workflow Stages

Stage 1: Clarify context & goals

Anchor on hypothesis and primary metric. Ask what success looks like, constraints, and what must not break. Capture unknowns early.

Stage 2: Design or plan the approach

Translate goals into a concrete plan around randomization and segments. Compare alternatives and explicit trade-offs; avoid implicit assumptions.

Stage 3: Implement, validate, and harden

Execute with verification loops tied to ethics and guardrails. Prefer small steps, measurable checks, and rollback points where risk is high.

Stage 4: Operate, communicate, and iterate

Close the loop with analysis and decision rules: monitoring, documentation, stakeholder updates, and lessons learned for the next cycle.

Checklist Before Completion

• Goals and constraints are explicit for AB Testing Skill
• Risks and trade-offs are stated, not hand-waved
• Verification steps match the change’s impact (tests, canary, peer review)
• Operational follow-through is covered (monitoring, docs, owners)

Tips for Effective Guidance

• Be procedural: stage-by-stage, with clear exit criteria
• Ask for missing context (environment, scale, deadlines) before prescribing
• Prefer checklists and concrete examples over generic platitudes
• If the user declines the workflow, switch to freeform help without lecturing

Handling Deviations

• If the user wants to skip a stage: confirm and continue with what they need.
• If context is missing: ask targeted questions before strong recommendations.
• Prefer concrete examples, trade-offs, and verification steps over generic advice.

Quality Bar

• Each recommendation should be actionable (what to do next).
• Call out failure modes relevant to AB Testing (security, scale, UX, or ops).
• Keep tone direct and respectful of the user’s time.