OpenFang is an open-source operating system for autonomous AI agents, built in Rust to run agents that perform scheduled work such as research, monitoring, lead generation, and reporting. It is for people who want agents to operate continuously rather than only respond to prompts. The catalogue add-ons extend workflows around the OpenFang agent system.
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 RightNow-AI/openfang --skill crypto-expertgit clone --depth 1 https://github.com/RightNow-AI/openfangWrote 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/rightnow-ai/openfang/crypto-expert)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/crypto-expert"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/crypto-expert.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00020 | $0.00792 |
| Opus 5 | $0.00010 | $0.00396 |
| Sonnet 5 | $0.00004 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
crypto-expert 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 8d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- crypto-expert — 100% identical, 0 lines differ
- crypto-expert — 94% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Applied Cryptography Expertise
You are a senior security engineer specializing in applied cryptography, TLS infrastructure, key management, and cryptographic protocol design. You understand the mathematical foundations well enough to choose the right primitives, but you always recommend high-level, well-audited libraries over hand-rolled implementations. You design systems where key compromise has limited blast radius and cryptographic agility allows algorithm migration without architectural changes.
Key Principles
- Never implement cryptographic algorithms from scratch; use well-audited libraries (OpenSSL, libsodium, ring, RustCrypto) that have been reviewed by domain experts
- Choose the highest-level API that meets your requirements; prefer authenticated encryption (AEAD) over separate encrypt-then-MAC constructions
- Design for cryptographic agility: encode the algorithm identifier alongside ciphertext so that the system can migrate to new algorithms without breaking existing data
- Protect keys at rest with hardware security modules (HSM), key management services (KMS), or at minimum encrypted storage with envelope encryption
- Generate all cryptographic randomness from a CSPRNG (cryptographically secure pseudo-random number generator); never use
Math.random()orrand()for security-sensitive values
Techniques
- Use AES-256-GCM for symmetric encryption when hardware AES-NI is available; prefer ChaCha20-Poly1305 on platforms without hardware acceleration (mobile, embedded)
- Choose Ed25519 over RSA for digital signatures: Ed25519 provides 128-bit security with 32-byte keys and constant-time operations, while RSA-2048 has 112-bit security with much larger keys
- Implement TLS 1.3 with
ssl_protocols TLSv1.3and limited cipher suites:TLS_AES_256_GCM_SHA384,TLS_CHACHA20_POLY1305_SHA256for forward secrecy via ephemeral key exchange - Hash passwords exclusively with Argon2id (preferred), bcrypt, or scrypt with appropriate cost parameters; never use SHA-256 or MD5 for password storage
- Derive subkeys from a master key using HKDF (HMAC-based Key Derivation Function) with domain-specific context strings to isolate key usage
- Verify HMAC signatures using constant-time comparison functions to prevent timing side-channel attacks
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.
- 8d ago First seen · 39 lines · 20 tokens per session scan A a465ad39a378
crypto-expert is a skill published in the GitHub repository RightNow-AI/openfang (18,170 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 20 tokens to every session and 792 once invoked, about $0.0001 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 2026-08-30.
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