get_error_logs

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

Annotations already declare readOnlyHint and non-destructive behavior; the description adds useful behavioral context beyond that: it is a monitoring endpoint, it costs no credits, it returns both BULK and REALTIME channels, and it includes request_id plus query_params for tracing failures. No contradiction with annotations.

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 front-loaded with the core purpose, then gives usage triggers, filter guidance, and a credit-cost note. Every paragraph earns its place; there is only minor overlap between the row-fields list and the filter examples, but nothing wasteful.

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 that there is no output schema, the description compensates by spelling out the returned columns, the two error channels, filtering options, tracing capability, and pricing behavior. For an 11-parameter optional-filter tool, this is sufficiently complete for an agent to select and call it correctly.

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 coverage is 100%, so the baseline is 3. The description adds meaning by explaining which filters matter most, giving concrete error_code examples like 'WEBHOOK_ERROR_404' and 'SOMETHING_WENT_WRONG', and clarifying the BULK vs REALTIME channel semantics. It does not deeply expand page/limit or date semantics, but the schema already covers those.

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-resource pair ('List the user's API request error logs') and anchors the output to the Errors page of the web app. It clearly distinguishes this tool from the sibling data tools by stating it covers both real-time API errors and bulk job errors with specific fields.

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 explicitly lists trigger phrasings such as 'why are my requests failing?' and 'show me recent errors', and gives the main filter strategy. It does not name when-not-to-use cases or alternative sibling tools, so it stops short of full routing guidance.

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