get_global_variable_value_by_name

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

No annotations are provided, so the description carries the full burden. It discloses that the tool reads values 'if known at compile-time', which is a key behavioral trait not evident from the schema. However, it lacks details on error handling, return format, or what happens if the variable isn't known at compile-time. For a read operation with no annotations, this is adequate but leaves gaps in transparency.

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 extremely concise and front-loaded: two sentences that directly state the purpose and usage guidance. Every sentence earns its place without redundancy or fluff, making it easy for an AI agent to parse quickly.

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 (a read operation with a compile-time constraint), no annotations, and no output schema, the description is minimally complete. It covers the core purpose and basic usage but lacks details on behavioral outcomes, error cases, or return values. This is adequate for a simple tool but could be improved for better agent understanding.

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% description coverage, with the parameter 'variable_name' clearly documented. The description doesn't add any parameter-specific semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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's purpose: 'Read a global variable's value (if known at compile-time)'. It specifies the verb ('Read'), resource ('global variable's value'), and a key constraint ('if known at compile-time'), which helps distinguish it from data_read_* functions. However, it doesn't explicitly differentiate from sibling tools like 'get_global_variable_value_at_address' or 'list_globals', leaving some ambiguity.

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 provides explicit guidance: 'Prefer this function over the `data_read_*` functions.' This gives clear context on when to use this tool versus alternatives, though it doesn't specify when NOT to use it (e.g., for non-compile-time values) or mention other siblings like 'get_global_variable_value_at_address'. The guidance is helpful but could be more comprehensive.

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