菜单
Reviewer for incentive structures. Identifies misalignments, principal-agent problems, perverse incentives, and second-order effects. Triggers: incentives, alignment, skin in the game, principal agent, perverse incentive, gaming, second order effects.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/chouswei/cursor-user-skills --skill incentive-alignment-reviewer命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Keep a working plan as MemNet session rows (campaign or plan task plus ordered step tasks with execution waves). Pin the live neighbourhood, then mutate to draft, update, or repolish. At plan time, mark which steps may run in parallel. Execute a ready wave via memnet-multitask when asked. Chat is a Shape of the graph, never the plan SSOT. Triggers: memnet plan, plan in memnet, update memnet plan, repolish plan, session plan, memnet planner, plan waves, parallel plan steps, execute plan wave. Skip: Markdown-only project-planner interview with no MemNet; building the MemNet engine.
Enforceable MemNet doctrine for Cursor Multitask Mode and Task sub-agents: one shared session SSOT, TCP or streamable-http transport, parent/worker MUST/MUSTNOT, MN-REQ-12 usage, system-dev two-store pattern for modelbasedPrj-*. Triggers: Multitask Mode, multitask, multi-agent, Task sub-agent, background worker, parent coordinator, delegate worker, shared session, memnet multitask, system-dev multitask, modelbasedPrj multitask, MN-REQ-12, parallel workers, TSK_* settle, TCP serve, streamable-http MCP, GQL wire, shaped pin_map.
How to use MemNet as mission working memory: goldfish loop, chat never SSOT, drop prior maps. Triggers: use memnet, how to use memnet, memnet goldfish, mission working memory, chat never SSOT, session graph.
基于 SOC 职业分类
正在显示 SKILL.md
| name | incentive-alignment-reviewer |
| description | Reviewer for incentive structures. Identifies misalignments, principal-agent problems, perverse incentives, and second-order effects. Triggers: incentives, alignment, skin in the game, principal agent, perverse incentive, gaming, second order effects. |
| metadata | {"pattern":"reviewer","version":"1.0-incentive","domain":"reasoning"} |
| pipeline_steps | 1. Inversion + Clarify - Identify the incentive structure, actors, rewards, and potential misalignments. 2. Principles Retrieval - Load references/incentive-review-checklist.md 3. Incentive Review - Apply checklist, identify risks and misalignments. 4. Self-Review & Iterate - Check completeness of analysis. Max 1 revision. 5. Final Output - Structured review using the checklist with findings and recommendations. |
| system_instruction | Respond in concise mode only. Use structured output. Keep analysis focused on incentives. |
| token_guardrails | - Context caching on incentive-review-checklist.md |
Role: Incentives, principal-agent, perverse incentives, second-order effects.
Run pipeline_steps; apply references/incentive-review-checklist.md rigorously.
Pairing: risk-assessor or decision-inverter.