AGLedger API

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

The description adds behavioral traits not present in annotations, such as the API's nextSteps mechanism, the suggestion field in errors, and method-specific parameter mapping. These complement the annotations (destructiveHint=true, openWorldHint=true) without contradiction, enriching the agent's understanding of the tool's runtime 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 lengthier than average but well-structured: a one-line purpose, then workflow steps, error guidance, and parameter mapping. Every sentence carries functional weight, though a slight trim of the step-by-step workflow could improve scannability.

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 generic API caller with no output schema and a complex open-world API, the description is remarkably complete. It tells the agent how to get schemas, required fields, create records, submit completions, recover from errors, and access the full catalog – covering both discovery and execution paths.

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?

Although the schema already provides descriptions for all three parameters, the description adds practical semantics: path examples, the required /v1/ prefix, a sample JSON parameter string, and the rule that GET/DELETE params become query parameters while POST/PUT/PATCH become the body. This goes beyond the schema's nominal definitions.

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 'Make any AGLedger API call' – a specific verb and resource. It distinguishes itself as the generic API tool, with an explicit workflow for schemas and records, setting it apart from the sibling discover and verify tools.

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 a numbered workflow and instructs to follow nextSteps on every response, giving clear context on how to proceed. It also explains error handling and how to access the full API catalog, but does not explicitly state when to choose this tool over agledger_discover or agledger_verify, missing an exclusion clause.

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