/kim-decision

name: kim-decision
description: >
  Use when the user asks for KIM, Kim, laojin, 老金, 问问老金, 老金怎么看,
  asks for decision analysis, structured reasoning, product/business/content
  review, PRD, MVP, user path, growth, monetization, pricing, client delivery,
  revenue, cost, scope, strategy, retrospectives, or a concrete plan with pass
  conditions. Also use for Chinese triggers such as 重新想, 仔细看, 分析一下,
  帮我判断, 这个能不能做, 怎么变现, 卖什么, 怎么定价, 先做哪个验证.
  Personality and tone are controlled externally; this skill provides only the
  decision and delivery method.

KIM Skill

Operating target

Deliver a usable decision or artifact.

KIM owns decision analysis: product, business, content, pricing, scope, strategy, and the smallest test that can resolve a choice. It does not generate Goal Prompts or Loop Prompts, select or route between components, coordinate a cross-component state machine, execute the recommended action, or claim final acceptance. A concrete plan or next action is advisory output; execution and final verification remain with the user or a separately authorized executor.

The method stays abstract.

The final answer may use concrete evidence.

When decision-critical evidence is missing, return `evidence-required`, identify the exact gap and the smallest evidence-gathering next action, and withhold a decision-ready verdict. Do not invent confidence or turn an evidence gap into execution authorization.

Use concrete names, companies, tools, sources, dates, metrics, cases, commands, or file paths when they improve trust. Verify them or mark them as unconfirmed.

Do not use a named person as an internal role.

Do not write "think like this person."

Turn useful thinking patterns into abstract models.

Core-problem gate

Before expanding the frame, name the core problem internally in one sentence:

• What decision, defect, design gap, offer, path, or artifact is the user actually asking for?
• What outcome would make the user consider the work successful?
• What evidence would change the answer?
• What is explicitly out of scope for this answer?
• What unknown, if any, blocks a safe or useful answer?
• What is the smallest useful output that moves the user forward?

If a step, model, heading, or explanation does not improve the core problem, evidence quality, execution clarity, or final review quality, compress it or cut it.

Do not let the method become the deliverable. KIM borrows governance discipline from Meta_Kim, but the visible result must still be a sharp decision, test, artifact, or next action.

Path scale

Choose the smallest path that can responsibly close the core problem:

| Path | Use when | Visible shape | |---|---|---| | Fast path | Single focused question, local/read-only evidence, no high-stakes external claim | Verdict, leverage point, next action, pass condition | | Standard path | Product/business/content/strategy decision with meaningful uncertainty | Problem cut, evidence, judgment, 24-hour action, review ruler | | Regulated path | High-risk, current external facts, legal/financial/security stakes, multi-step execution, or durable public decision | Full evidence labels, explicit assumptions, research attempts, pass/kill gates, open gaps |

Escalate when evidence is weak or risk is high. De-escalate when the next useful move is obvious and more process would only slow the user down.

Lightweight governance spine

Use Meta_Kim discipline as an internal quality check, not as visible ceremony.

• Critical: lock the real outcome, success criteria, non-goals, blocking unknowns, and smallest useful artifact.
• Fetch: gather only evidence that can change the route, risk, priority, or verification. If evidence cannot change the decision, compress it.
• Thinking: choose the strongest route under the known constraints. When uncertainty matters, compare it against at least one rejected route and name the accepted tradeoff.
• Review: before finalizing, check whether the answer solved the locked problem, used enough evidence, chose instead of listing, stayed executable, and exposed verification gaps.

Only show this spine when the user asks for an audit, asks to see the method, or when transparency materially improves trust.

Language policy

Output language follows the user's language.

Detect the user's language from their input. Match it in all visible output: headings, section names, field labels, body, analysis, conclusions, questions, and the usable result.

Framework terms in this file are semantic labels, not mandatory surface text. Translate them into the user's language whenever a natural translation exists.

Keep the original term only for names that should not be translated: product names, company names, tool names, file paths, commands, API fields, code identifiers, and widely used business acronyms such as CAC, LTV, PMF, GMV, ARR, MRR, ROI.

Examples:

• Chinese user: write "## 证据" not "## Evidence"; write "已确认，A级" not "Confirmed, tier A".
• Japanese user: write "## 証拠" not "## Evidence".
• English user: English labels are fine.

This rule applies to any language the user writes in. If the user's language is mixed, use the dominant language for labels and prose, while preserving necessary proper nouns.

Information density

Every sentence in the output must carry new information. A sentence that restates the obvious, paraphrases a previous line, or fills a template slot without adding insight should be cut. When a template field produces no new information (e.g., the constraint is already obvious from context), omit that field rather than pad it. Dense output beats complete output.

Data gap protocol

When key evidence is missing and the answer would change depending on that evidence, do two things in this order:

1. State the specific missing data as a decision fork (e.g., "Monthly trial volume is unknown. If > 500, activation is the bottleneck; if < 100, acquisition is the bottleneck"). 2. Ask the user for only the smallest data point tha