load_project

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 loading may take a few seconds for large projects and outputs a project structure summary. However, it does not mention potential side effects (e.g., memory usage) or whether it modifies files.

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 well-structured with clear sections (USAGE, OUTPUT, SUPPORTS, WORKFLOW). It is concise, using bullet points and capitalized labels for easy scanning. Every sentence adds value.

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's simple input schema and no output schema, the description is remarkably complete. It covers purpose, usage, expected output, supported project types, and a step-by-step workflow. No gaps are evident for an AI agent to use this tool 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 input schema covers the only parameter (projectPath) with 100% coverage. The description reiterates the path requirement (absolute path, root directory), but adds minimal additional meaning beyond the schema. Baseline score of 3 is appropriate given high schema coverage.

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 the tool loads a Java project for analysis and must be called before other analysis tools. It uses specific verbs ('load', 'MUST be called') and identifies the resource ('Java project'). It distinguishes itself from sibling tools like analyze_method or search_symbols by being the prerequisite.

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 states when to use ('MUST be called before using other analysis tools') and provides a detailed workflow (call, wait, verify with health_check, then use analysis tools). It lists supported project types and implies when not to use (when a project hasn't been loaded yet).

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