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egoughnour

Massive Context MCP

by egoughnour

rlm_firewall_status

Check code execution firewall status: verify if enabled, dangerous code blocking, Ollama endpoint, embedding model, similarity threshold, and Ollama reachability.

Instructions

Check the status of the code execution firewall.

Returns information about whether the firewall is enabled, the Ollama endpoint being used, and whether dangerous code patterns will be blocked.

The firewall is auto-enabled when code-firewall-mcp is installed: pip install massive-context-mcp[firewall]

Returns: { "enabled": bool, "package_installed": bool, "ollama_url": str, "embedding_model": str, "similarity_threshold": float, "ollama_reachable": bool, }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the firewall is auto-enabled upon installation and describes the return fields. It does not mention side effects (likely none) and is consistent with a read operation.

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 brief, front-loaded with the purpose, and every sentence is informative. It includes a clear return format without unnecessary verbiage.

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?

Given zero parameters and a well-described output schema in the description, the tool definition is completely self-sufficient. It covers what the tool does, what it returns, and how the firewall is enabled.

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

Parameters5/5

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

The input schema has 0 parameters and 100% coverage. The description adds significant value by specifying the exact return structure (enabled, package_installed, ollama_url, etc.) beyond what the schema provides. Baseline for 0 params is 4, and the rich return type warrants a 5.

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 checks the status of the code execution firewall and lists the specific information returned (enabled, package_installed, ollama_url, etc.). This is a specific verb+resource that distinguishes it from siblings like rlm_ollama_status or rlm_system_check.

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

Usage Guidelines3/5

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

It implies usage for checking firewall status but does not explicitly state when to use this versus alternatives like rlm_system_check. No guidance on prerequisites or exclusion criteria.

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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