sharp-edges

sharp-edges is a skill for Claude Code, Codex from NOMARJ/sigil. It costs 68 tokens per session (710 once invoked), scanned A, original, Apache-2.0.

A code-review check that finds APIs, settings, and coding patterns that are valid but often cause security or reliability problems.

In plain words
What is it for?
Use it when reviewing code for dangerous patterns or asking whether an implementation is safe.
Why use it?
It helps catch hidden risks such as unsafe input handling, injection bugs, and race conditions before they become incidents.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it when reviewing code for dangerous patterns or asking whether an implementation is safe.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nomarj/sigil/sharp-edges
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.

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

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for sharp-edges

README.md
[![agentmods](https://agentmods.dev/badge/skills/nomarj/sigil/sharp-edges/github.svg)](https://agentmods.dev/skills/nomarj/sigil/sharp-edges)
Your own site
<a href="https://agentmods.dev/skills/nomarj/sigil/sharp-edges"><img src="https://agentmods.dev/badge/skills/nomarj/sigil/sharp-edges/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.

agentmods 80×15 button for sharp-edges

Your own site · 80×15
<a href="https://agentmods.dev/skills/nomarj/sigil/sharp-edges"><img src="https://agentmods.dev/badge/skills/nomarj/sigil/sharp-edges.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 710 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00068 $0.00710
Opus 5.5 $0.00027 $0.00284
Sonnet 5.5 $0.00014 $0.00142
Haiku 4.5 $0.00007 $0.00071

Measured 1mo ago against content hash 5900c1ff1a63, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sharp-edges scanned grade A with 1 finding 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 1mo 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- `subprocess.call(shell=True)` or `os.system()` with string interpolation
packs/security/skills/owasp-security/sharp-edges/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sharp Edges Detector

Adapted from Trail of Bits' sharp-edges skill. Identifies API usage patterns and code constructs that are technically valid but frequently lead to security vulnerabilities or reliability failures.

What You're Looking For

Dangerous Function Calls

  • eval(), exec(), Function() with user-controlled input
  • innerHTML, dangerouslySetInnerHTML with unsanitized data
  • subprocess.call(shell=True) or os.system() with string interpolation
  • pickle.loads(), yaml.load() (unsafe deserializer), JSON.parse() on untrusted input without schema validation
  • Math.random() or random.random() for security-sensitive operations (use crypto.randomBytes or secrets module)

SQL and Injection Vectors

  • String concatenation or template literals in SQL queries
  • ORM raw query methods with unparameterized input
  • LDAP, XPath, or command injection via string interpolation
  • GraphQL queries built from user input without validation

Concurrency and Race Conditions

  • TOCTOU (Time-of-Check-Time-of-Use) patterns: checking a condition and acting on it in separate operations
  • Shared mutable state without synchronization
  • Non-atomic read-modify-write sequences
  • File operations without proper locking

Path and File Operations

  • Path construction from user input without canonicalization
  • Directory traversal via ../ in user-supplied paths
  • Symlink following without verification
  • Temporary file creation with predictable names

Cryptographic Footguns

  • MD5 or SHA1 for password hashing (use bcrypt, scrypt, or argon2)
  • ECB mode for encryption
  • Hardcoded IVs or nonces
  • Custom cryptographic implementations
  • Insufficient key lengths

Type and Memory Safety

  • Unchecked type assertions/casts
  • Integer overflow in arithmetic used for allocation or indexing
  • Buffer operations without bounds checking
  • Null pointer dereference patterns

Scan Protocol

1. Parse the changed files into AST (or analyze textually for config files)
2. Walk the AST looking for known dangerous patterns
3. For each finding, assess:
   - Is the input user-controlled? (worse) or internal? (less bad)
   - Is there sanitization/validation nearby? (might be OK)
   - Is this in a test file? (lower severity)
4. Classify and report

Read the full file on GitHub · 80 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. 1mo ago First seen · 80 lines · 68 tokens per session scan A 5900c1ff1a63

Subscribe to this mod's changes

sharp-edges is a skill published in the GitHub repository NOMARJ/sigil (6 stars, last pushed 11d ago), licensed Apache-2.0. It adds 68 tokens to every session and 710 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.