Oh My Posh Validator

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool validates configurations but does not describe what happens during validation (e.g., error reporting, success indicators, or output format). For a validation tool with zero annotation coverage, this is a significant gap 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 a single, efficient sentence with zero waste. It front-loads the core purpose and includes essential details (supported formats) without unnecessary elaboration, making it highly concise and well-structured.

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 lack of annotations and output schema, the description is incomplete. It does not explain what the validation returns (e.g., errors, success status) or behavioral aspects like error handling. For a tool with 2 parameters and no structured output information, the description should provide more context to guide the agent effectively.

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 100%, so the schema already documents both parameters thoroughly. The description adds minimal value by mentioning supported formats, which aligns with the 'format' parameter's enum, but does not provide additional syntax or usage details beyond what the schema specifies. Baseline 3 is appropriate 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?

The description clearly states the specific action ('validate') and target resource ('an oh-my-posh configuration against the schema'), distinguishing it from the sibling tool 'validate_segment' which likely validates a different component. It also specifies the supported formats, making the purpose highly specific and differentiated.

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 no guidance on when to use this tool versus alternatives, such as the sibling 'validate_segment'. It mentions supported formats but does not explain scenarios where validation is needed or prerequisites for usage, leaving the agent without contextual direction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions validation but doesn't describe what happens on success/failure (e.g., returns validation errors, boolean result), any rate limits, or authentication needs. For a validation tool with zero annotation coverage, this leaves significant gaps in understanding its 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?

The description is concise and well-structured with two sentences: the first states the purpose, and the second provides usage context. Every sentence adds value without redundancy, making it front-loaded and efficient.

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 annotations and no output schema, the description is incomplete for a validation tool. It doesn't explain what the tool returns (e.g., validation results, errors), behavioral traits, or error handling. The schema covers inputs well, but overall context is lacking for effective agent use.

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 100%, so the schema already documents both parameters ('format' and 'content') with descriptions and enums. The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints. Baseline 3 is appropriate 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?

The description clearly states the tool's purpose: 'Validate a segment snippet against the oh-my-posh schema.' It specifies the verb (validate) and resource (segment snippet), but doesn't explicitly differentiate from its sibling tool 'validate_config' beyond mentioning 'individual prompt segments' versus 'configuration.'

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 implied usage guidance: 'Useful for validating individual prompt segments before adding them to a configuration.' This suggests when to use it (before adding to config) but doesn't explicitly state when to use this versus the sibling 'validate_config' or any exclusions. It offers some context but lacks clear alternatives or when-not-to-use details.

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