scenario-analysis

scenario-analysis is a skill for Claude Code from vivy-yi/finance-skills. It costs 95 tokens per session (2,597 once invoked), scanned A, original, MIT.

A financial planning method that compares baseline, optimistic, and pessimistic assumptions to estimate their effects on returns, cash flow, or valuation.

In plain words
What is it for?
It helps assess major investments, prepare strategic plans and budgets, estimate the effect of price or cost shocks, and perform sensitivity analysis.
Why use it?
It shows how a decision may change when important conditions, such as revenue growth, margins, interest rates, or material costs, move up or down.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions CLAUDE.md.

Good fit It helps assess major investments, prepare strategic plans and budgets, estimate the effect of price or cost shocks, and perform sensitivity analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vivy-yi/finance-skills/scenario-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add vivy-yi/finance-skills --skill scenario-analysis
Clone the repo
git clone --depth 1 https://github.com/vivy-yi/finance-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for scenario-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/vivy-yi/finance-skills/scenario-analysis/github.svg)](https://agentmods.dev/skills/vivy-yi/finance-skills/scenario-analysis)
Your own site
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/scenario-analysis"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/scenario-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for scenario-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/scenario-analysis"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/scenario-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,597 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00095 $0.02597
Opus 5 $0.00048 $0.01299
Sonnet 5 $0.00019 $0.00519
Haiku 4.5 $0.00010 $0.00260

Measured 11d ago against content hash b62461ef445a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

scenario-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

finance-skills/skills/capital-allocation/skills/scenario-analysis/SKILL.md · 278 lines

How it starts

The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.

加载上下文

首次使用时: 读取 ../../CLAUDE.md 获取场景级配置(情景定义标准/历史基准/概率估算方法)。


/scenario-analysis — 情景分析

Examples

→ 示例:用户说"帮我做一个三种情景的财务预测:乐观/基准/悲观",系统应调用本技能,执行三情景财务预测分析。

→ 示例:用户说"原材料价格暴涨 30% 对我们明年利润的影响有多大",系统应调用本技能,执行价格冲击敏感性分析。

→ 示例:用户说"竞争者价格战开始了,帮我评估对我们的影响",系统应调用本技能,执行竞争情景分析。

第一步:分析框架确定

分析标的与范围:

□ 分析对象:[项目/业务单元/公司]
□ 分析维度:[财务回报/现金流/估值/战略影响]
□ 币种:[CNY]

□ 关键假设变量([X] 个):
  → 变量 1:[收入增长率] — 基准 [X]%
  → 变量 2:[毛利率] — 基准 [X]%
  → 变量 3:[利率/折现率] — 基准 [X]%
  → 变量 4:[...] — 基准 [...]

情景数量与定义:

□ 情景结构:
  → 情景 1:基准情景(最可能发生)
  → 情景 2:乐观情景(上行情景)
  → 情景 3:悲观情景(下行情景)
  → [情景 4:极端悲观(如需)]
  → [情景 5:极端乐观(如需)]

□ 情景概率分配:
  → 基准:[X]%
  → 乐观:[X]%
  → 悲观:[X]%
  → 合计:100%

第二步:基准情景设计

基准情景假设:

□ 宏观经济假设:
  → GDP 增速:[X]%
  → 行业增速:[X]%
  → 利率水平:[X]%

□ 业务假设:
  → 收入增长率:[X]%([假设依据])
  → 毛利率:[X]%([假设依据])
  → 运营费用率:[X]%
  → 资本支出:[X] 万/年

□ 财务预测([X] 年):
  → Year 1:收入 [X] 万,EBITDA [X] 万
  → Year 2:收入 [X] 万,EBITDA [X] 万
  → Year 3:收入 [X] 万,EBITDA [X] 万

基准情景财务结果:

□ 核心指标:
  → NPV:[X] 万 [✅ > 0 / 🔴 < 0]
  → IRR:[X]%(vs 门槛 [X]%)[✅ > 门槛 / 🔴 < 门槛]
  → 回收期:[X] 年

□ 自由现金流(FCF):
  → Year 1:[X] 万
  → Year 2:[X] 万
  → Year 3:[X] 万
  → 累计 FCF:[X] 万

第三步:乐观/悲观情景设计

乐观情景假设(较基准 [+/-X]%):

□ 假设变化:
  → 收入增长率:[X]%(基准 [X]%,提升 [X]%)
  → 毛利率:[X]%(基准 [X]%,提升 [X]%)
  → 运营费用率:[X]%(基准 [X]%,降低 [X]%)

□ 乐观情景财务结果:
  → NPV:[X] 万
  → IRR:[X]%
  → 概率:[X]%

悲观情景假设(较基准 [-X]%):

□ 假设变化:
  → 收入增长率:[X]%(基准 [X]%,下降 [X]%)
  → 毛利率:[X]%(基准 [X]%,下降 [X]%)
  → 运营费用率:[X]%(基准 [X]%,上升 [X]%)

□ 悲观情景财务结果:
  → NPV:[X] 万 [🔴 < 0]
  → IRR:[X]%([🔴 < 门槛])
  → 概率:[X]%

情景对比汇总:

| 情景 | 收入增长率 | 毛利率 | NPV(万) | IRR | 概率 |
|------|----------|--------|----------|-----|------|
| 乐观 | [X]% | [X]% | [+X] | [X]% | [X]% |
| 基准 | [X]% | [X]% | [X] | [X]% | [X]% |
| 悲观 | [X]% | [X]% | [-X] | [X]% | [X]% |

第四步:概率加权分析

期望值(概率加权 NPV)计算:

□ 期望 NPV = Σ (情景 NPV × 概率)

  = ([X] 万 × [X]%) + ([X] 万 × [X]%) + ([-X] 万 × [X]%)
  = [X] 万 + [X] 万 + [-X] 万
  = [X] 万

□ 期望 NPV > 0:[✅ 期望值为正 / 🔴 期望值为负]

□ NPV 下行风险:
  → 悲观情景 NPV:[-X] 万
  → 概率加权下行损失:[X] 万

Read the full file on GitHub · 278 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 278 lines · 95 tokens per session scan A b62461ef445a

Subscribe to this mod's changes

scenario-analysis is a skill published in the GitHub repository vivy-yi/finance-skills (28 stars, last pushed 2mo ago), licensed MIT. It adds 95 tokens to every session and 2,597 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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