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 martinholovsky/claude-skills-generator --skill encryptiongit clone --depth 1 https://github.com/martinholovsky/claude-skills-generatorWrote 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/martinholovsky/claude-skills-generator/encryption)<a href="https://agentmods.dev/skills/martinholovsky/claude-skills-generator/encryption"><img src="https://agentmods.dev/badge/skills/martinholovsky/claude-skills-generator/encryption/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/martinholovsky/claude-skills-generator/encryption"><img src="https://agentmods.dev/badge/skills/martinholovsky/claude-skills-generator/encryption.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 | $0.00000 | $0.04182 |
| Opus 5 | $0.00000 | $0.02091 |
| Sonnet 5 | $0.00000 | $0.00836 |
| Haiku 4.5 | $0.00000 | $0.00418 |
Grade A, and why
encryption 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 9d 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 — 499 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Encryption Skill
name: encryption version: 1.0.0 domain: security/cryptography risk_level: HIGH languages: [python, typescript, rust, go] frameworks: [sqlcipher, cryptography, libsodium] requires_security_review: true compliance: [GDPR, HIPAA, PCI-DSS, SOC2] last_updated: 2025-01-15
MANDATORY READING PROTOCOL: Before implementing ANY encryption, read
references/advanced-patterns.mdfor key derivation andreferences/security-examples.mdfor implementation patterns.
1. Overview
1.1 Purpose and Scope
This skill provides secure-by-default patterns for implementing encryption in JARVIS AI Assistant, covering:
- SQLCipher: Encrypted SQLite database with AES-256-GCM
- Argon2id: Memory-hard key derivation function
- Key Management: Secure generation, storage, rotation, and destruction
- Secure Memory: Protection against memory disclosure attacks
1.2 Risk Assessment
Risk Level: HIGH
Justification:
- Cryptographic failures expose all protected data
- Key compromise leads to complete confidentiality loss
- Implementation errors are catastrophic and often undetectable
- Regulatory violations (GDPR, HIPAA, PCI-DSS) carry severe penalties
Attack Surface:
- Key derivation weaknesses
- Insecure random number generation
- Timing side-channels
- Memory disclosure (cold boot, crash dumps)
- Key reuse across contexts
2. Core Responsibilities
2.1 Primary Functions
- Encrypt data at rest using AES-256-GCM with authenticated encryption
- Derive keys securely using Argon2id with appropriate parameters
- Manage key lifecycle including rotation, escrow, and destruction
- Protect key material in memory and during operations
- Integrate with OS keychains for master key storage
2.2 Core Principles
- TDD First - Write tests before implementation; test encryption/decryption round-trips, authentication failures, and edge cases
- Performance Aware - Cache derived keys, use streaming for large data, leverage hardware acceleration
- Security by Default - Use authenticated encryption modes, memory-hard KDFs, secure random sources
- Defense in Depth - Multiple layers of protection, fail securely, minimize key exposure
What ships with it
3 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.
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.
- 9d ago First seen · 499 lines · 0 tokens per session scan A 548ade689fa6
encryption is a skill published in the GitHub repository martinholovsky/claude-skills-generator (45 stars, last pushed 9mo ago), licensed Unlicense. It costs nothing until one of its globs matches a file; then it loads 4,182 tokens. 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 2026-08-30.
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