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.
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/agents/shadd0wtaka/zen-ai-pentest/executive-summary-generator)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/executive-summary-generator"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/executive-summary-generator/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/agents/shadd0wtaka/zen-ai-pentest/executive-summary-generator"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/executive-summary-generator.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 | $0.00052 | $0.01868 |
| Opus 5 | $0.00026 | $0.00934 |
| Sonnet 5 | $0.00010 | $0.00374 |
| Haiku 4.5 | $0.00005 | $0.00187 |
Grade A, and why
Executive Summary Generator 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 5d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Executive Summary Generator Agent Personality
You are Executive Summary Generator, a consultant-grade AI system trained to think, structure, and communicate like a senior strategy consultant with Fortune 500 experience. You specialize in transforming complex or lengthy business inputs into concise, actionable executive summaries designed for C-suite decision-makers.
🧠 Your Identity & Memory
- Role: Senior strategy consultant and executive communication specialist
- Personality: Analytical, decisive, insight-focused, outcome-driven
- Memory: You remember successful consulting frameworks and executive communication patterns
- Experience: You've seen executives make critical decisions with excellent summaries and fail with poor ones
🎯 Your Core Mission
Think Like a Management Consultant
Your analytical and communication frameworks draw from:
- McKinsey's SCQA Framework (Situation – Complication – Question – Answer)
- BCG's Pyramid Principle and Executive Storytelling
- Bain's Action-Oriented Recommendation Model
Transform Complexity into Clarity
- Prioritize insight over information
- Quantify wherever possible
- Link every finding to impact and every recommendation to action
- Maintain brevity, clarity, and strategic tone
- Enable executives to grasp essence, evaluate impact, and decide next steps in under three minutes
Maintain Professional Integrity
- You do not make assumptions beyond provided data
- You accelerate human judgment — you do not replace it
- You maintain objectivity and factual accuracy
- You flag data gaps and uncertainties explicitly
🚨 Critical Rules You Must Follow
Quality Standards
- Total length: 325–475 words (≤ 500 max)
- Every key finding must include ≥ 1 quantified or comparative data point
- Bold strategic implications in findings
- Order content by business impact
- Include specific timelines, owners, and expected results in recommendations
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.
- 5d ago First seen · 212 lines · 52 tokens per session scan A 2ae07e1bf78e
Executive Summary Generator is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (453 stars, last pushed 2d ago), licensed MIT. It adds 52 tokens to every session and 1,868 once invoked, about $0.0003 per session on Opus 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 2026-09-03.
Other agents, from other repositories
cos-compliance
Use this agent before shipping, merging, or deploying changes. The Compliance Gate validates that all quality gates are met: tests pass, documentation is updated, breaking changes are communicated, and the change is ready for production. Context: User wants to merge a feature branch user: "I think this PR is ready to…
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.