get_supported_zones
List all bidding-zone codes supported by GridPulse with friendly country names. Call this when the user’s zone is ambiguous or after a ZONE_NOT_FOUND error.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List all bidding-zone codes supported by GridPulse with friendly country names. Call this when the user’s zone is ambiguous or after a ZONE_NOT_FOUND error.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly communicates the read-only nature (list) and expected output (zone codes with country names). While it doesn't mention edge cases like pagination or all zones being returned, the phrase 'all bidding-zone codes' covers scope comprehensively enough for a simple lookup tool.
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 short sentences, front-loaded with the primary purpose, followed by a directly usable usage case. Every word earns its place, with no filler or redundant phrasing.
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 simplicity (zero params, no output schema), the description covers the needed context: what the tool returns and when to use it. It doesn't detail return structure, but the description inherently implies a list of zone codes with country names. The guidance about ZONE_NOT_FOUND error adds situational completeness, though a tiny gap remains about whether the list is static or time-dependent.
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?
There are no parameters, so the schema has 100% coverage vacuously. The description adds no parameter-specific detail, but with zero parameters, none is needed. Baseline 4 is appropriate because there are no parameter semantics to clarify.
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 uses a specific verb ('List') and clearly defines the resource ('all bidding-zone codes supported by GridPulse') and output ('with friendly country names'). It is distinct from sibling tools like get_current_price or get_carbon_intensity, which focus on data retrieval rather than zone enumeration.
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 states when to invoke the tool: 'when the user’s zone is ambiguous or after a ZONE_NOT_FOUND error.' This provides clear context and differentiates it from other tools that operate on a specific zone, making it easy for an agent to select the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.