analyze

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It explains that the tool analyzes code but does not state whether it is read-only, destructive, or requires authentication. No side effects or limitations are mentioned.

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 a clear opening line and bullet-pointed modes. It is front-loaded with the general purpose. Some redundancy exists (repeating 'Parameters:' for each mode), but overall it is reasonably concise.

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 complexity (multi-mode, 11 parameters) and lack of annotations, the description is incomplete. It does not describe return values despite an output schema existing, and it omits details for several parameters such as 'workspace_path' and 'include_project_structure'.

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 must compensate. While parameters are grouped by mode, their meanings are not explained beyond names (e.g., 'sql_content', 'selected_text'). The description adds little value for understanding parameter usage or constraints.

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 analyzes SQL or PySpark code for context, data flow, or optimization opportunities. It further defines four distinct modes (sql_context, data_flow, codebase, workspace), each with a specific purpose, which distinguishes it from sibling tools like 'context' or 'optimize' that might be more focused.

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 lists modes and associated parameters but provides no guidance on when to use this tool versus alternatives like sibling tools 'context', 'optimize', or 'review'. There is no mention of prerequisites, exclusions, or decision criteria for choosing a mode.

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