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 Njones17/AI-agent-master-cyber-skills-list --skill implementing-digital-signatures-with-ed25519git clone --depth 1 https://github.com/Njones17/AI-agent-master-cyber-skills-listWrote 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/njones17/ai-agent-master-cyber-skills-list/implementing-digital-signatures-with-ed25519)<a href="https://agentmods.dev/skills/njones17/ai-agent-master-cyber-skills-list/implementing-digital-signatures-with-ed25519"><img src="https://agentmods.dev/badge/skills/njones17/ai-agent-master-cyber-skills-list/implementing-digital-signatures-with-ed25519/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/njones17/ai-agent-master-cyber-skills-list/implementing-digital-signatures-with-ed25519"><img src="https://agentmods.dev/badge/skills/njones17/ai-agent-master-cyber-skills-list/implementing-digital-signatures-with-ed25519.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 | $0.00050 | $0.00635 |
| Opus 5 | $0.00025 | $0.00318 |
| Sonnet 5 | $0.00010 | $0.00127 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
implementing-digital-signatures-with-ed25519 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
4 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 · 64 lines · 50 tokens per session scan A 86e7a509c773
implementing-digital-signatures-with-ed25519 is a skill published in the GitHub repository Njones17/AI-agent-master-cyber-skills-list (21 stars, last pushed 6mo ago), with no licence file. It adds 50 tokens to every session and 635 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 skills, from other repositories
implementing-digital-signatures-with-ed25519
Ed25519 is a high-performance digital signature algorithm using the Edwards curve Curve25519. It provides 128-bit security with 64-byte signatures and 32-byte keys, offering significant advantages ove.
implementing-jwt-signing-and-verification
JSON Web Tokens (JWT) defined in RFC 7519 are compact, URL-safe tokens used for authentication and authorization in web applications. This skill covers implementing secure JWT signing with HMAC-SHA256.
implementing-zero-knowledge-proof-for-authentication
Zero-Knowledge Proofs (ZKPs) allow a prover to demonstrate knowledge of a secret (such as a password or private key) without revealing the secret itself. This skill implements the Schnorr identificati.
jwt-algorithm-confusion
Identify and exploit Algorithm Confusion vulnerabilities in JSON Web Tokens (JWT). This skill details how to bypass signature verification by changing the signing algorithm from asymmetric (RS256) to symmetric (HS256) and using the public key as the symmetric secret.
delegate
Cryptographic delegation for AI agents. Scope-confines what Claude Code can do in this session using Ed25519 delegation tokens. Every action is verified before execution and signed for the audit trail. Use when asked to "delegate", "restrict scope", "authorize", or "sudo mode".
audit
View the kanoniv-auth audit trail. Shows every action the agent took - delegations, scope verifications, tool calls, and results. Filter by agent, action type, or time range. Use when asked to "show audit log", "what happened", "show the trail", or "audit".