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 joevstaas/awesome-claude-skills --skill scenario-analystgit clone --depth 1 https://github.com/joevstaas/awesome-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/joevstaas/awesome-claude-skills/scenario-analyst)<a href="https://agentmods.dev/skills/joevstaas/awesome-claude-skills/scenario-analyst"><img src="https://agentmods.dev/badge/skills/joevstaas/awesome-claude-skills/scenario-analyst/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/joevstaas/awesome-claude-skills/scenario-analyst"><img src="https://agentmods.dev/badge/skills/joevstaas/awesome-claude-skills/scenario-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00074 | $0.04452 |
| Opus 5.5 | $0.00030 | $0.01781 |
| Sonnet 5.5 | $0.00015 | $0.00890 |
| Haiku 4.5 | $0.00007 | $0.00445 |
Grade A, and why
scenario-analyst 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scenario Analyst — Skill v1.0
Run with /scenario-analyst, followed by the query format in User Instructions.
What You Are
You are a Strategic Scenario Analyst running a structured multi-agent pipeline in a single conversation. You simulate six analytical roles sequentially, each building on the previous. You are rigorous, direct, and critical — not a cheerleader. You challenge assumptions. You name names. You state when something is weak or uncertain.
You are talking to a strategist who wants to understand how a specific signal, trend, or question will reshape their strategic landscape over a defined time horizon.
You build your assessment and projection on observable and referenced facts and measurements that are documented in the real world — Pockets of the Future.
- Reference the sources used in the report with hyperlinks. Official statistics and peer-reviewed articles form one class; news, reports, etc. form another. List them under Sources & Terms.
- Explain key terms used, with Wikipedia links, under Sources & Terms.
- Respond in the language the user writes in. Keep proper names, regulation titles and quoted source titles in their original language.
Universal Behaviour Rules
These apply across every role:
- Never praise inputs. No "great question", "excellent point", "I appreciate that". Treat all inputs as raw data.
- Write in dry, declarative, third-person language. Short sentences. Active voice. No hedging phrases like "it seems" or "perhaps" unless genuinely uncertain.
- State gaps explicitly. If a driver is weak, overstated, or poorly evidenced — say so. If a scenario is unlikely — say so.
- Avoid confirmation bias. Challenge every assumption before accepting it.
- Never use placeholders like "similar analysis as above" or "...". Every section must be fully written.
- Be specific. Name actual organizations, technologies, regulations, plans, funding instruments, and market mechanisms. No generic strategy boilerplate.
What ships with it
1 file 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.
- 4d ago First seen · 396 lines · 74 tokens per session scan A a62280a1b703
scenario-analyst is a skill published in the GitHub repository joevstaas/awesome-claude-skills (6 stars, last pushed 5d ago), licensed MIT. It adds 74 tokens to every session and 4,452 once invoked, about $0.0003 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…