skills/ HoangNguyen0403/agent-skills-standard

product-experimentation

Design and validate bounded product experiments with falsifiable hypotheses, precommitted thresholds, guardrail metrics, ethical eligibility, and stop rules; use for product hypothesis validation / product experiment design. (triggers: `product hypothesis validation`, `product experiment design`)

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Product Experimentation

Priority: P0 (CRITICAL)

Design and validate product experiments with strict falsifiability, precommitted decision thresholds, guardrail monitoring, and bounded exposure, ensuring honest routing of negative and inconclusive findings.

1. Capability Preflight

Verify installed evidence capabilities before designing or reviewing experiments:

  • Resolve product-evidence from <agent-skill-root>/product-management/product-evidence/SKILL.md (ordinary install), <agent-skill-root>/product-management-product-evidence/SKILL.md (flattened Kiro install), or MCP get_skill("product-management", "product-evidence"). Distinguish an explicitly excluded pack from a missing pack; if host configuration cannot establish which, report unknown.
  • Separately check installed scripts/validate-product-evidence.mjs, its package-local assets/product-evidence.schema.json, and Node >=20. Missing script/schema/runtime blocks validation, not safe proposal drafting. MCP body access is not proof that local executable resources are installed.
  • Missing AUTH/DEC, consent, eligible data, or measurement query/baseline is an authority/data gap, not a runtime failure. Keep the experiment proposed and state the missing input; never simulate validation, install dependencies, or fabricate authorization.

2. Core Protocol

  1. Falsifiable Hypotheses (HYP):
    • Formulate clear predictions, causal mechanisms, target cohorts, and explicit disconfirmation criteria matching normative ledger schema.
  2. Precommitted Success & Failure Thresholds:
    • Establish explicit numeric rules (rules: { success, failure, inconclusive }) before running.
    • Modifying thresholds or moving goalposts after observing interim data is strictly prohibited.
  3. Primary Metric & Guardrails:
    • Designate exactly one primary decision metric (MET ref {id, revision}).
    • Define guardrails (guardrails: [{id, revision}]). An uncontained guardrail breach halts the experiment immediately.
  4. Finite Exposure, Budget, and Duration:
    • Declare strict bounds: bounds: { starts_at, ends_at, budget_cap, currency, exposure_cap, stop_rules }.
    • exposure_cap must be a finite safe integer ($\ge 0$); budget_cap must be an unsigned decimal string.
  5. Ethical Eligibility & Stop Rules:
    • Enforce user consent, non-maleficence, and privacy rules.
    • Pre-commit automated stop rules for severe regressions or ethical breaches.
  6. Authorization & Lifecycle Boundaries:
    • Ledger Eligibility vs Host Authorization: An authorized EXP record in the ledger confirms eligibility, NOT live permission to expose users, spend funds, or mutate production flags. Actual production changes require current authenticated host/operator control.
    • Approver names in JSON metadata never substitute for verified ledger authority (AUTH).
    • Separately retain the frozen experiment plan. Result progression adds MET/SRC evidence and completed EXP.result: { classification, sources, limitations }.
    • Any material change to predictions, telemetry queries, guardrails, budget, or exposure requires a new authorized experiment revision.
  7. Honest Decision Routing (DEC):
    • Supported: Propose investment review (purpose: "investment", outcome: "propose"). Does not auto-authorize build.
    • Refuted: Recommend stopping further work, bounded iteration, or proposal as supported by evidence. For a purpose: "experiment" DEC use only lawful outcomes such as "propose", "defer", or "reject"; "stop" is valid only for purpose: "value_review" when its required strategy, authority, and artifact evidence exists. Otherwise record a proposal and the missing proof; never fabricate a recorded value-review decision.
    • Inconclusive: Defer or bounded further learning (outcome: "defer"). Never treat inconclusive results as validation.
    • Immutable recorded DECs stay current until superseded by a new recorded DEC ID referencing supersedes: {id, revision}.

3. Anti-Patterns & Red Flags

  • No Moving Thresholds: Never lower success bars after seeing weak results.
  • No Unconditional Full Build: Never claim positive prototype testing authorizes full implementation without budget approval.
  • No Ignoring Guardrails: Never celebrate conversion increases if churn or error guardrails are breached.
  • No Fabricated Authorization: Never treat JSON strings or ledger eligibility as live host authorization.
  • No In-Place Decision Mutation: Never edit an already recorded decision in place.

4. References

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