GTech Networks DB: get reasoning/insertion pattern

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

No annotations are provided, but the description clearly indicates a read-only fetch operation ('Get a documented reasoning recipe'). It does not mention any destructive side effects, authorization needs, or rate limits, but the nature of the tool is transparently a retrieval.

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 a single, front-loaded sentence that states the scope, action, and purpose with examples. Every part adds value; no redundant or wasted words.

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 simple one-parameter tool with no output schema, the description adequately explains what the tool does and provides usage examples. It could mention the return format, but this is minor given the tool's clarity.

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 has 100% coverage for the single parameter 'topic', providing an example. The description adds value by giving additional concrete topic examples ('reordering', 'new-approval-step'), which helps the agent understand valid inputs beyond the schema's example.

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 specifies the tool fetches a reasoning recipe for database changes, scoped to GTech/Hexagon HxGN NetWorks Core, with concrete examples (e.g., inserting a row, reordering columns). This clearly distinguishes it from sibling tools like get_table_schema or get_glossary_term.

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 implies usage by providing examples of when to use (e.g., 'how to insert a new row', 'how to reorder/renumber'), but does not explicitly state when not to use or provide alternative tools for other tasks. Usage context is implied rather than explicit.

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