generate_client_config

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

With no annotations, the description carries the full burden. It discloses the core behavior of writing config files and explicitly explains dry_run behavior ('Return config entries and paths without writing files'), which implies the alternative (writing files when dry_run is false). It also clarifies which params apply to which transports and what tool_search_mode does (adds an environment variable). It does not mention side effects like overwriting existing files or directory creation, but for a generation tool this is a reasonable level of disclosure.

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 front-loaded with the purpose sentence, then a compact list of parameters. Each line delivers necessary information without filler. Given that the schema has zero descriptions, the list is appropriately sized and not redundant. The format (name, meaning, defaults) is scannable and efficient.

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?

For a tool with 12 parameters, 0 required, and no schema descriptions, the description provides everything an agent needs: purpose, parameter semantics, transport-specific behavior, and dry-run functionality. An output schema exists, so return values need not be explained. No essential information is missing for correct invocation.

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 description coverage is 0%, so the description fully compensates. It explains every parameter's meaning, allowed values (client: all/codex/cursor/vscode/claude_code/gemini; transport: stdio/streamable-http/sse), defaults (base_dir defaults to repo root), and transport-specific effects (python_command/server_script/tool_search_mode for stdio; mcp_host/mcp_port for HTTP/SSE). This is a complete, non-redundant parameter reference.

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 immediately states a precise verb and resource: 'Generate MCP client config files' for a specific set of clients (Codex, Cursor, VS Code, Claude, Gemini). This clearly distinguishes it from sibling tools, which are all Unreal editor operations, and leaves no ambiguity about the tool's function.

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 context is clear from the tool name and description that this is the tool for generating MCP client configs. It does not explicitly mention alternatives or exclusions, but among the large sibling list, no other tool overlaps in purpose. The parameter details further imply the intended use cases (e.g., different transports, dry-run). A slight gap is the lack of an explicit 'when to use' or 'when not to use' statement, but the context is unambiguous.

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