TabletopExercise

TabletopExercise is a skill for Claude Code, Codex from SecurityTalent/bugskill-ai. It costs 64 tokens per session (5,597 once invoked), scanned A, original, MIT.

A cybersecurity tabletop-exercise framework for planning, running, and evaluating simulated security incidents. A tabletop exercise is a discussion-based rehearsal in which technical and executive teams respond to a realistic scenario.

In plain words
What is it for?
Use it to create executive, technical, or cross-functional scenarios; generate executable simulated actions for exercise runners; and produce gap analyses and improvement plans.
Why use it?
It helps organizations expose missing procedures, playbooks, coordination steps, and decision-making before a real incident occurs.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is --data ../exercises/[slug]/exercise-data.json \.

Good fit Use it to create executive, technical, or cross-functional scenarios; generate executable simulated actions for exercise runners; and produce gap analyses and improvement plans.

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Install

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.

Clone the repo
git clone --depth 1 https://github.com/SecurityTalent/bugskill-ai
agentmods
npx agentmods add skills/securitytalent/bugskill-ai/tabletopexercise

Made for: Claude Code, Codex.

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 TabletopExercise

README.md
[![agentmods](https://agentmods.dev/badge/skills/securitytalent/bugskill-ai/tabletopexercise/github.svg)](https://agentmods.dev/skills/securitytalent/bugskill-ai/tabletopexercise)
Your own site
<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.

agentmods 80×15 button for TabletopExercise

Your own site · 80×15
<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>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,597 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 $0.00064 $0.05597
Opus 5.5 $0.00026 $0.02239
Sonnet 5.5 $0.00013 $0.01119
Haiku 4.5 $0.00006 $0.00560

Measured 1mo ago against content hash 52bb0bbb3a27, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 3 executable files (pdf-generator/generate-html-standalone.ts, pdf-generator/generate-html.ts, pdf-generator/generate-pdf.ts), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Awesome-Claude-Code-Agent-Skills/10-DevSecOps-and-Defense/TabletopExercise/SKILL.md · 640 lines

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

Read the full file on GitHub · 640 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. 1mo ago First seen · 640 lines · 64 tokens per session scan A 52bb0bbb3a27

Subscribe to this mod's changes

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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