get_server_environment

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

With no annotations provided, the description fully discloses the tool's behavior: it returns the Python executable path, version, and installed versions of every package. No side effects are expected; it is a read-only inspection tool, and the description accurately reflects that.

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 concise, consisting of two short sentences that front-load the purpose. Every sentence serves a clear function: stating what it returns and when to use it. No unnecessary words.

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?

Given the tool has no parameters and no output schema, the description is complete. It explains exactly what the tool returns and provides usage context. No additional information is needed for an agent to use it 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?

The tool has zero parameters, so there are no parameters to describe. The baseline for no parameters is 4. The description does add value by explaining the return values, which is relevant but falls under parameter semantics only indirectly.

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 it inspects the MCP server's Python environment, listing the Python executable path, version, and installed packages. This distinguishes it from sibling tools like get_installed_package_version and list_packages, which have narrower scopes.

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 tells when to use the tool (to verify the correct environment before asking about specific packages) and what to do if a package is not installed (update command in .vscode/mcp.json). This provides clear context and actionable guidance.

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