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Validate Implementation

mcp_m7_validate_implementation

Validate code against safety patterns and best practices for a specified technology, with optional strict rules, suggested fixes, and risk metrics.

Instructions

Validate code implementation against safety patterns and best practices

Input Schema

NameRequiredDescriptionDefault
codeYesCode to validate
technologyYesTechnology/language of the code (e.g., javascript, typescript, python)
strict_modeNoEnable strict validation mode
custom_rulesNo
include_fixesNoInclude suggested fixes in response
risk_thresholdNoMinimum risk score to report issues (0-100)
include_metricsNoInclude detailed metrics in response
enabled_categoriesNo
confidence_thresholdNoMinimum confidence level for patterns (0.0-1.0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.18.1

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden, yet it never says whether the tool is read-only, whether it modifies code, or what the report contains. It also leaves undefined how strict_mode, risk_threshold, and confidence_threshold change behavior, which matters for a 9-parameter analysis tool.

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?

A single front-loaded sentence with no filler, so it is efficient. The brevity is a weakness in coverage rather than verbosity, which is penalized in contextual completeness instead.

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

Completeness2/5

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

For a 9-parameter tool with no annotations and no output schema, the description omits the return shape (issues, fixes, metrics, scores) and the effect of the threshold parameters. An agent can call it, but cannot predict what it gets back or how to tune it.

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

Parameters2/5

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

Schema description coverage is 78%, just below the baseline-3 threshold, and two parameters (enabled_categories and the custom_rules object structure) have no description at all. The description adds nothing about parameters, missing the chance to explain categories or rule shape.

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

Purpose4/5

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

States a specific verb ('Validate') and resource ('code implementation') plus the criteria (safety patterns and best practices). It does not distinguish itself from close siblings such as mcp_m7_validate, mcp_m7_safety_verify, or mcp_m7_style_guardian, so an agent cannot tell from the description alone which validator to pick.

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 guidance on when to use this versus the many sibling validation tools, and no exclusions or prerequisites. With six-plus validator-like siblings in the list, the absence of routing guidance is a real gap.

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