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Check Injection

check_injection
Read-onlyIdempotent

Scan source code for SQL injection, command injection, and path traversal vulnerabilities caused by unsanitized input or unsafe string concatenation. Supports Python, JavaScript, Java, Go, Ruby, and other languages.

Instructions

Scan source code for injection vulnerabilities: SQL injection, command injection, path traversal via unsafe string concatenation/unsanitized input. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect input-handling bugs; for secrets use check_secrets. Companion code-security tools: check_secrets (hard-coded credential detection), check_dependencies (known-CVE vulnerability audit), check_headers (live HTTP security-header validation), scan_headers (live HTTP scan via domain). Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesSource code string to scan for injection vulnerabilities (can be a single file or code snippet)
languageNoProgramming language of the code. Must be one of: python, javascript, typescript, java, go, ruby, shell, bash, generic. Use 'generic' if unsure.generic

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate read-only and non-destructive. The description adds behavioral context: 'No data stored' and details rate limits (Free: 30/hr, Pro: 500/hr), going beyond annotations to disclose important operational traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured paragraph that front-loads the purpose and efficiently packs essential information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (injection scanning), the description covers purpose, usage, behavioral traits, parameters, and output format. The output schema exists, so the return description is supplemental. Complete enough for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%. The description adds value by listing the supported languages and explaining the 'generic' option, which supplements the enum and descriptions in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans source code for injection vulnerabilities (SQL injection, command injection, path traversal) and lists supported languages. It distinguishes from sibling tools by mentioning companion tools like check_secrets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use to detect input-handling bugs; for secrets use check_secrets' and lists other companion tools. It also provides context about rate limits and output format, but does not explicitly state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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