Recent pipeline logs

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

The description supplements the readOnlyHint, idempotentHint, and openWorldHint annotations by detailing the return format (structured rows with timestamp, level, service, message, trace_id/report_id). No contradictions. However, it could mention that no log data is modified.

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 sentences: the first covers the tool's core action and scope, the second covers return format and usage. Every word is functional; no redundancy or filler.

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?

Despite the lack of an output schema, the description fully explains the return rows, filter parameters, and use cases. For a log retrieval tool, this is complete and actionable.

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?

With 100% schema description coverage, the description still adds value by clarifying each parameter's format ('ISO-8601', 'max 200', default values, valid enum entries) and purpose. For example, it explains 'service' options and 'level' severity order.

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 ('Pull'), identifies the resource ('recent log entries from the Mushi pipeline services'), and lists the exact services. It clearly distinguishes from sibling tools like get_pipeline_run or get_recent_reports.

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 explicit use cases: 'when a fix failed, a QA story keeps erroring, or an ingest pipeline went silent.' While it doesn't mention when not to use or name alternatives, the context is clear enough for an agent to decide.

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