跳到正文
cccskills
免费在 GitHub 公开

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`)

中文简介正在准备中。当前显示原文说明。

实测评分 未实测

查看安装方法

包含的文件(13)

  • SKILL.md5.6 KB
  • evals/evals.json7.3 KB
  • references/citations-and-sources.md2.0 KB
  • references/ethical-and-stop-rules.md3.2 KB
  • references/evidence-mapping.md7.2 KB
  • references/experimentation-protocol.md6.9 KB
  • references/semantic-rubrics.md4.5 KB
  • references/synthetic-authorization-v1.md519 B
  • references/synthetic-authorization-v2.md1.1 KB
  • references/synthetic-lifecycle.json29.3 KB
  • references/synthetic-observations-v1.md569 B
  • references/synthetic-plan-v1.md1.1 KB
  • references/synthetic-plan-v2.md2.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Upgrade an Android project to Android Gradle Plugin (AGP) 9. Use when migrating to AGP 9, updating Gradle build files, migrating to built-in Kotlin, or adopting the new AGP DSL.

中文简介正在准备中。当前显示原文说明。

HoangNguyen0403/agent-skills-standard5812026年10月24日 更新

Apply Clean Architecture layering, modularization, and Unidirectional Data Flow in Android projects. Use when setting up project structure, placing code in layers, configuring feature/core modules, or implementing UDF patterns; defer Compose state and ViewModel/StateFlow implementation to their specific skills.

中文简介正在准备中。当前显示原文说明。

HoangNguyen0403/agent-skills-standard5812026年10月24日 更新

Implement WorkManager and background processing correctly on Android. Use when creating Worker classes, scheduling tasks, choosing between WorkManager and Foreground Services, or setting up Hilt in workers; defer FCM and notification delivery to android-notifications.

中文简介正在准备中。当前显示原文说明。

HoangNguyen0403/agent-skills-standard5812026年10月24日 更新

Build high-performance declarative UI with Jetpack Compose. Use when writing Composable functions, optimizing recomposition, hoisting state, or working with LazyColumn and side effects; defer deep-link and navigation routing to android-navigation.

中文简介正在准备中。当前显示原文说明。

HoangNguyen0403/agent-skills-standard5812026年10月24日 更新

Migrate an Android XML View to Jetpack Compose following a structured 10-step workflow. Use when converting XML layouts to Compose, setting up Compose in an existing View-based project, or incrementally adopting Compose.

中文简介正在准备中。当前显示原文说明。

HoangNguyen0403/agent-skills-standard5812026年10月24日 更新

Write correct coroutine scopes, lifecycle collection, and dispatcher injection in Android production code. Use for suspend functions, coroutine scopes, and dispatcher mechanics; defer ViewModel StateFlow/LiveData architecture, Fragment lifecycle recipes, persistence/notifications, and unit-test recipes to their specific skills.

中文简介正在准备中。当前显示原文说明。

HoangNguyen0403/agent-skills-standard5812026年10月24日 更新

查看 HoangNguyen0403 的全部技能

报告此技能的问题