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SECRET4422

GuardRail MCP v2.0 (Enterprise)

by SECRET4422

audit_code_safety

Scan source code with hybrid multi-engine analysis to detect security vulnerabilities, secrets, and code issues, and receive a risk score and security verdict.

Instructions

Hybrid multi-engine scan: secrets regex, Python AST + advanced multi-hop taint, tree-sitter structural sinks, language grids, custom rules/plugins. Returns redacted issues, engines used, risk score, security_verdict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hybridNoUse full hybrid engine (recommended).
use_astNo
filenameNo
languageNo
tenant_idNo
use_taintNo
source_codeYes
use_pluginsNo
use_treesitterNo
Behavior3/5

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

No annotations are provided, so description bears full burden. It explains the multi-engine approach and that results are redacted, which is a behavioral trait. However, it does not disclose whether the tool is read-only, error behavior, or potential side effects. Some transparency but not exhaustive.

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?

Single sentence that efficiently conveys the core purpose, engine types, and return structure. No unnecessary words; every part earns its place. Front-loaded with 'Hybrid multi-engine scan'.

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

Completeness3/5

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

No output schema exists, but description lists return values (redacted issues, engines, risk score, security_verdict). However, with 9 parameters and many undocumented, the description does not explain how parameters like language or filename affect scanning, nor clarify single-file vs repo-level scanning compared to siblings like scan_repository.

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 low (11%), only 'hybrid' has a description. The description indirectly explains boolean parameters like use_ast, use_taint, use_plugins, use_treesitter by mentioning those engines. However, it does not describe filename, language, tenant_id, or how source_code is used beyond being required. Adds some meaning but not fully compensating.

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 it performs a 'Hybrid multi-engine scan' for security issues in source code, listing specific engines (secrets regex, Python AST taint, tree-sitter sinks, language grids, custom plugins) and return values. This differentiates it from sibling tools like scan_repository (repo-level) and audit_cloud_cost (cost-related).

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. Does not mention prerequisites, when not to use, or contrast with siblings like scan_dependencies or scan_git_diff. Usage context is only implied by the description.

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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