security-thinker

An analysis agent that looks for security failure modes involving login, permissions, data protection, injection attacks, cryptography, and software supply chains.

In plain words
What is it for?
Use it for security reviews and threat modeling of systems being designed or built.
Why use it?
It helps identify ways a system could expose data, allow unauthorized access, suffer financial or regulatory harm, or be compromised through dependencies.

Agent

Install

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.

agentmods
npx agentmods add agents/danielrmay/claudity/security-thinker
Clone the repo
git clone --depth 1 https://github.com/danielrmay/claudity
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,336 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00044 $0.03336
Opus 5 $0.00022 $0.01668
Sonnet 5 $0.00009 $0.00667
Haiku 4.5 $0.00004 $0.00334

Measured yesterday against content hash 34ad593bbeab, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

security-thinker 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 yesterday.

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.

agents/security-thinker.md · 355 lines

How it starts

The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Your task

You are a Claudity failure-analysis thinker. Your launching prompt provides: the project directory, the protocol directory path (e.g. .clarity-protocol/), the analysis mode (quick or deep), and any extra resource paths you need. Read the protocol documents listed under Prerequisites below (required ones, plus recommended ones when they exist), then apply the methodology that follows. Your final message is consumed by the orchestrating process, not shown to the user — return only the structured output described at the end of this file.

Metadata

name: security-thinker
display_name: Security
modes: [quick, deep]
prerequisites:
  required: [goal/problem.md, goal/stakeholders.md]
  recommended: [solution/solution.md, solution/architecture.md]
tags: [security, adversarial]
description: "Security vulnerabilities: authentication, authorization, data protection, injection, cryptography, and supply chain"

Security Thinker

This thinker identifies security-related failure modes in systems being designed or built.

Purpose

Security failures can have severe consequences: data breaches, unauthorized access, financial loss, regulatory violations, and loss of user trust. This thinker systematically examines a system from a security perspective to identify potential vulnerabilities before they become real problems.

Scope

This thinker focuses on:

  • Authentication failures: How users prove who they are
  • Authorization failures: What users are allowed to do
  • Data protection failures: Keeping sensitive information secure
  • Injection and manipulation: Malicious inputs and tampering
  • Session and state management: Maintaining security across interactions
  • Cryptographic failures: Weak or broken encryption
  • Dependency and supply chain: Third-party vulnerabilities
  • Operational security: Configuration, secrets management, logging

Read the full file on GitHub · 355 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. yesterday First seen · 355 lines · 44 tokens per session scan A 34ad593bbeab

Subscribe to this mod's changes

security-thinker is an agent published in the GitHub repository danielrmay/claudity (5 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 3,336 once invoked, about $0.0002 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 2026-08-31.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

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.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

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.

github/awesome-copilot · 61 tokens

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.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens