export_security_context

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description's statement 'Read-only' is consistent but redundant. However, it adds value by detailing the output structure (JSON with specific fields) and the analysis scope (call graphs, security categories), going beyond annotations.

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

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

The description is three sentences, front-loaded with the core purpose, and every sentence adds value. It wastes no words and is easy to parse.

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

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

The tool has no output schema, so the description compensates by listing the return structure. It also mentions usage context (pre-installation analysis). It could be slightly clearer about the project scope, but overall it is complete enough for an AI agent to use correctly.

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

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

Schema coverage is 100% with descriptions for both parameters (scope and depth). The description adds no new semantic information beyond what the schema provides (e.g., 'relative to project root' and 'default: 3'). Baseline score of 3 is appropriate as the schema already does the heavy lifting.

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

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

The description clearly states that the tool exports a security context for MCP server analysis, generating a specific enrichment JSON. It lists the key components (tool registrations, call graphs, sensitive data flows, etc.), which distinguishes it from sibling tools like scan_security or get_call_graph by focusing on a pre-installation security analysis output.

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

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

The description explicitly says 'Use to analyze MCP server security before installation,' providing clear guidance on when to use the tool. It does not explicitly mention when not to use it or list alternatives, but the context is sufficient for an AI agent to understand its primary purpose.

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