claude-skills is a large collection of reusable skills, commands, plugins, and supporting resources for coding agents across engineering, business, research, compliance, and productivity work. It is used by people who want agents such as Claude Code, Codex, Gemini CLI, or Cursor to follow specialized workflows. The catalogue contains selected skills and settings from the collection.
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.
npx skills add alirezarezvani/claude-skills --skill scenario-war-roomgit clone --depth 1 https://github.com/alirezarezvani/claude-skillsWrote 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.
[](https://agentmods.dev/skills/alirezarezvani/claude-skills/scenario-war-room)<a href="https://agentmods.dev/skills/alirezarezvani/claude-skills/scenario-war-room"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-skills/scenario-war-room/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.
<a href="https://agentmods.dev/skills/alirezarezvani/claude-skills/scenario-war-room"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-skills/scenario-war-room.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.01957 |
| Opus 5.5 | $0.00024 | $0.00783 |
| Sonnet 5.5 | $0.00012 | $0.00391 |
| Haiku 4.5 | $0.00006 | $0.00196 |
Grade A, and why
scenario-war-room 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 today.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- scenario-war-room — 92% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scenario War Room
Model cascading what-if scenarios across all business functions. Not single-assumption stress tests — compound adversity that shows how one problem creates the next.
Keywords
scenario planning, war room, what-if analysis, risk modeling, cascading effects, compound risk, adversity planning, contingency planning, stress test, crisis planning, multi-variable scenario, pre-mortem
Quick Start
python scripts/scenario_modeler.py # Interactive scenario builder with cascade modeling
Or describe the scenario in natural language:
"What if we lose our top customer AND miss the Q3 fundraise?" "What if 3 engineers quit AND we need to ship by Q3?" "What if our market shrinks 30% AND a competitor raises $50M?"
What This Is Not
- Not a single-assumption stress test (that's
/em:stress-test) - Not financial modeling only — every function gets modeled
- Not worst-case-only — models 3 severity levels
- Not paralysis by analysis — outputs concrete hedges and triggers
Framework: 6-Step Cascade Model
Step 1: Define Scenario Variables (max 3)
State each variable with:
- What changes — specific, quantified if possible
- Probability — your best estimate
- Timeline — when it hits
Variable A: Top customer (28% ARR) gives 60-day termination notice
Probability: 15% | Timeline: Within 90 days
Variable B: Series A fundraise delayed 6 months beyond target close
Probability: 25% | Timeline: Q3
Variable C: Lead engineer resigns
Probability: 20% | Timeline: Unknown
Step 2: Domain Impact Mapping
For each variable, each relevant role models impact:
| Domain | Owner | Models |
|---|---|---|
| Cash & runway | CFO | Burn impact, runway change, bridge options |
| Revenue | CRO | ARR gap, churn cascade risk, pipeline |
| Product | CPO | Roadmap impact, PMF risk |
| Engineering | CTO | Velocity impact, key person risk |
| People | CHRO | Attrition cascade, hiring freeze implications |
| Operations | COO | Capacity, OKR impact, process risk |
| Security | CISO | Compliance timeline risk |
| Market | CMO | CAC impact, competitive exposure |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today First seen · 224 lines · 59 tokens per session scan A bbc259eb11e8
scenario-war-room is a skill published in the GitHub repository alirezarezvani/claude-skills (28,607 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 1,957 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-24.
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