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check_injection

Read-onlyIdempotent

Scan source code for injection vulnerabilities like SQL, command, and path traversal by detecting unsafe string concatenation and unsanitized input. Supports multiple programming 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, non-destructive, idempotent. Description adds rate limits, return format, and 'no data stored' policy, which go beyond annotations without contradiction.

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

Conciseness4/5

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

Packed with essential info: purpose, vulnerability types, languages, usage guidance, rate limits, return format. Slightly long but every sentence adds value.

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

Completeness5/5

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

Covers all relevant aspects: input, languages, usage guidance, rate limits, return type, data policy. Output schema exists, so return format mention is sufficient.

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

Parameters3/5

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

Schema coverage is 100% with clear descriptions for both parameters. The description lists supported languages again but adds no significant new meaning beyond 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?

States it scans for injection vulnerabilities (SQL, command, path traversal) with specific languages. Clearly distinguishes from siblings like check_secrets and check_dependencies.

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

Usage Guidelines5/5

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

Explicitly says when to use (detect input-handling bugs) and when not (for secrets use check_secrets). Lists companion tools and their purposes.

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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