analyze_schema

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

No annotations are provided, so the description must cover behavioral disclosure. It conveys a read-only, local analysis behavior ('without an org connection') but lacks explicit details on side effects, performance, or error conditions. The mention of outputs adds some transparency, but not comprehensive.

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?

Two sentences, front-loaded with the main function and followed by a use-case note. Every sentence contributes value, with no redundancy.

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 no output schema, the description lists the output types (SObject definitions, field usage heatmaps, relationship graphs), providing a useful overview. It could elaborate on output structure or limitations but is adequate for an agent to decide 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 covers both parameters (directory and includeHeatmap) with 100% coverage, meeting the baseline. The description adds no extra semantics beyond what schema provides.

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 aggregates and analyzes the inferred schema from Apex classes, with specific outputs (SObject definitions, field usage heatmaps, relationship graphs). This distinguishes it from sibling tools focused on scanning, testing, and rule management.

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?

It provides clear context: 'Useful for understanding the data model without an org connection,' indicating when to use. However, it doesn't explicitly mention alternatives or exclusions, so it stops short of full guidance.

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