Scenario Analysis
Build scenario and sensitivity analysis - bull/base/bear cases and sensitivity tables on key drivers. Use to stress-test a model, valuation, or forecast and show the range of outcomes.
Install
$ agentstack add skill-m-binimran-finance-pack-scenario-analysis ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-m-binimran-finance-pack-scenario-analysis) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
scenario-analysis
One number is a guess; a range with drivers is analysis. Show what swings the outcome.
Process
- Identify the key drivers that move the result most (growth, margin, WACC, multiple, churn).
- Sensitivity: vary one (or two, as a table) and show the output's response - e.g. value per share across a
WACC x terminal-growth grid. This exposes how fragile the answer is.
- Scenarios: coherent bull / base / bear - each a consistent set of assumptions (not just +/- 10%),
with a brief story for why.
- Probability-weight (optional): rough odds on each scenario for an expected value - clearly subjective.
- Takeaway: the range of outcomes, what you'd need to believe for each, and the asymmetry (up vs. down).
Output
- A sensitivity table + bull/base/bear scenarios (assumptions + outputs) + the key swing factors and the
risk/reward asymmetry. All labeled as estimates.
Guardrails
- Scenarios are estimates with stated assumptions (
projections-assumptions). - Don't present the base case as "the answer" - the point is the range and what drives it.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: m-binimran
- Source: m-binimran/finance-pack
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.