Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/SecurityTalent/bugskill-ainpx agentmods add skills/securitytalent/bugskill-ai/tabletopexerciseWrote 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/securitytalent/bugskill-ai/tabletopexercise)<a href="https://agentmods.dev/skills/securitytalent/bugskill-ai/tabletopexercise"><img src="https://agentmods.dev/badge/skills/securitytalent/bugskill-ai/tabletopexercise/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/securitytalent/bugskill-ai/tabletopexercise"><img src="https://agentmods.dev/badge/skills/securitytalent/bugskill-ai/tabletopexercise.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 | $0.00064 | $0.05597 |
| Opus 5.5 | $0.00026 | $0.02239 |
| Sonnet 5.5 | $0.00013 | $0.01119 |
| Haiku 4.5 | $0.00006 | $0.00560 |
Grade A, and why
TabletopExercise 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 1mo 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 — 640 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TabletopExercise Skill
Purpose
Design, facilitate, and evaluate cybersecurity tabletop exercises (TTX) for technical and executive audiences. Generate realistic scenarios, technical atomics for runners, and identify organizational gaps in incident response capabilities.
When to Use
- Designing tabletop exercise scenarios for SOC teams or executives
- Creating technical "atomics" (executable injects) for scenario runners
- Generating checklists to identify missing SOPs, playbooks, or procedures
- Evaluating incident response plan effectiveness
- Building cross-functional coordination exercises
- Post-exercise gap analysis and improvement planning
Key Capabilities
1. Scenario Generation
- Executive Scenarios: Business impact focus, decision-making, communication strategies
- Technical Scenarios: Detailed detection/response, forensics, technical challenges
- Hybrid Scenarios: Cross-functional coordination exercises
- AI-Enhanced: Deepfake attacks, automated threat chains, supply chain compromise
2. Technical Atomics for Runners
Exercise facilitators receive executable atomics - specific technical actions to simulate during scenarios:
Example Atomic Set (Ransomware Scenario):
T+0min: Send initial phishing email to participant's test inbox
T+15min: Simulate EDR alert: "Suspicious PowerShell execution on DESKTOP-01"
T+30min: Inject: Backup system shows "Replication failed - destination unreachable"
T+45min: Deliver ransom note via simulated file share
T+60min: Simulate CEO email inquiry: "Why can't I access the sales database?"
3. SOP/Playbook Gap Analysis
Automatically generates checklists identifying missing procedures:
Example Output:
MISSING PLAYBOOKS IDENTIFIED:
□ Ransomware Response Playbook
- Detected mentions of: encryption, ransom, backup restoration
- No documented procedure found for: crypto-ransomware containment
□ Executive Communication Protocol
- Scenario requires CEO notification
- Missing: Executive notification checklist, approval thresholds
□ Vendor Breach Response
- Third-party compromise scenario element present
- Missing: Vendor incident coordination runbook
What ships with it
15 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.
- ATOMICS-LIBRARY.md 26 KB
- exercises/rainbow-six-ddos-attack/exercise-data.json 76 KB
- exercises/rainbow-six-ddos-attack/Rainbow-Six-DDoS-Attack-Tabletop.html 212 KB
- exercises/rainbow-six-ddos-attack/README.md 7.2 KB
- pdf-generator/generate-html-standalone.ts 619 B runs code
- pdf-generator/generate-html.ts 67 KB runs code
- pdf-generator/generate-pdf.ts 50 KB runs code
- pdf-generator/package.json 582 B
- pdf-generator/README.md 13 KB
- pdf-generator/SSRF-AWS-Credential-Compromise-Tabletop.html 211 KB
- pdf-generator/SSRF-AWS-Credential-Compromise-Tabletop.pdf 580 KB
- pdf-generator/ssrf-exercise-data.json 53 KB
- pdf-generator/styles/print.css 18 KB
- pdf-generator/templates/tabletop-exercise.html 27 KB
- README.md 22 KB
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.
- 1mo ago First seen · 640 lines · 64 tokens per session scan A 52bb0bbb3a27
TabletopExercise is a skill published in the GitHub repository SecurityTalent/bugskill-ai (13 stars, last pushed 21d ago), licensed MIT. It adds 64 tokens to every session and 5,597 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 2026-08-31.
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