sharp-edges

A security-focused review workflow for finding APIs, configurations, and interfaces that make mistakes easy. It applies the idea that the safest option should also be the easiest option.

In plain words
What is it for?
Use it when reviewing API or library designs, security-related settings, cryptographic interfaces, authentication, authorization, and similar developer-facing controls.
Why use it?
It helps identify insecure defaults and confusing choices before they lead to vulnerabilities.

Skill for Claude CodeCodex

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 skills/stefaniuk/loadout/sharp-edges
Any agent
npx skills add stefaniuk/loadout --skill sharp-edges
Clone the repo
git clone --depth 1 https://github.com/stefaniuk/loadout

Made for: Claude Code, Codex.

Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,582 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod 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 $0.00074 $0.02582
Opus 5 $0.00037 $0.01291
Sonnet 5 $0.00015 $0.00516
Haiku 4.5 $0.00007 $0.00258

Measured yesterday against content hash 3b69a709c2f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sharp-edges 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.

Origin

This is a copy

91% identical to sharp-edges — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/skills/sharp-edges/skills/sharp-edges/SKILL.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sharp Edges Analysis

Evaluates whether APIs, configurations, and interfaces are resistant to developer misuse. Identifies designs where the "easy path" leads to insecurity.

When to Use

  • Reviewing API or library design decisions
  • Auditing configuration schemas for dangerous options
  • Evaluating cryptographic API ergonomics
  • Assessing authentication/authorization interfaces
  • Reviewing any code that exposes security-relevant choices to developers

When NOT to Use

  • Implementation bugs (use standard code review)
  • Business logic flaws (use domain-specific analysis)
  • Performance optimization (different concern)

Agent

The sharp-edges-analyzer agent runs the full sharp edges analysis workflow autonomously. Use it when you want a dedicated analysis of APIs, configurations, or interfaces for misuse resistance and footgun potential. The agent follows the four-phase workflow (Surface Identification, Edge Case Probing, Threat Modeling, Validate Findings) and reads language-specific references on demand.

Core Principle

The pit of success: Secure usage should be the path of least resistance. If developers must understand cryptography, read documentation carefully, or remember special rules to avoid vulnerabilities, the API has failed.

Rationalizations to Reject

Rationalization Why It's Wrong Required Action
"It's documented" Developers don't read docs under deadline pressure Make the secure choice the default or only option
"Advanced users need flexibility" Flexibility creates footguns; most "advanced" usage is copy-paste Provide safe high-level APIs; hide primitives
"It's the developer's responsibility" Blame-shifting; you designed the footgun Remove the footgun or make it impossible to misuse
"Nobody would actually do that" Developers do everything imaginable under pressure Assume maximum developer confusion
"It's just a configuration option" Config is code; wrong configs ship to production Validate configs; reject dangerous combinations
"We need backwards compatibility" Insecure defaults can't be grandfather-claused Deprecate loudly; force migration

Read the full file on GitHub · 294 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 · 294 lines · 74 tokens per session scan A 3b69a709c2f8

Subscribe to this mod's changes

sharp-edges is a skill published in the GitHub repository stefaniuk/loadout (1 stars, last pushed 3d ago), licensed MIT. It adds 74 tokens to every session and 2,582 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to sharp-edges, differing in 12 lines, and is treated as a copy.