export logs

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

Beyond the readOnly/idempotent annotations, the description discloses numerous non-obvious behaviors: the 10,000-row cap with no limit/offset, the X-Omnia-Export-Capped truncation header, skipped malformed rows rather than failures, a 409 when request logging is disabled, and exclusion of aborted exchanges. These add real context beyond what annotations provide, and there is no contradiction.

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 long but every clause earns its place: endpoint, auth scope, response content type, line format, ordering, headers, cap behavior, malformed-row handling, and error shape. It is front-loaded with the core purpose and then layers operational specifics without redundancy.

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?

With no output schema present, the description fully compensates by detailing the JSONL body format, headers, error cases, truncation detection, and filter advice. An agent has everything needed to invoke and interpret the result 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 description coverage is 100%: all 7 parameters (start, end, model, tag, segment, cache_hit, finish_reason) have individual descriptions in the schema. The tool description adds general filtering context (e.g., 'narrow the filter') but does not elaborate on individual parameters, so the schema carries the burden; baseline 3 is appropriate.

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 opens with 'Export the filtered logged exchanges as JSONL in chat format', naming the verb, resource, and output format in one precise sentence. It further specifies the assistant reply appended and the training/eval use case, which cleanly distinguishes it from siblings like list_logs or export_audit_log without needing to inspect their schemas.

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?

It clearly states the intended use case ('ready to pipe into your own training or eval tooling') and gives actionable advice when the cap is hit ('narrow the filter, e.g. a time range'). However, it does not explicitly name sibling alternatives or state when not to use this tool, leaving some inference to the agent.

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