describe_analysis

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

With no annotations, the description carries the behavioral burden. It usefully discloses the return contents (properties, methods, enum constants) and implies a read-only introspection, but says nothing about side effects such as whether it spins up a STATISTICA process, runtime cost, or how the 'attach' live-edit mode changes behavior.

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 tightly packed sentences with zero waste; the core action and the enumerated return are front-loaded, and the workflow cue (building a run_analysis request) follows.

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?

With no output schema and no annotations, the description correctly compensates by stating what the call returns and where it fits in the run_analysis workflow. The remaining gap is the absence of any side-effect or process/latency context for an introspection call.

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 75%, so most parameters (path, attach, module) are documented in the schema itself. The description adds no additional parameter meaning, so the baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb (introspect) and resource (a STATISTICA analysis dialog), and enumerates exactly what it returns: settable properties, callable methods, and known enum constants. It also implicitly distinguishes itself from run_analysis by positioning itself as the upstream step.

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?

Explicitly tells the agent when to reach for it: 'before driving it' and 'Use it to build a run_analysis request', which routes it against the run_analysis sibling. It stops short of naming when NOT to use it or listing other alternatives such as list_analysis_modules.

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