get_provenance_records

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds the content breakdown by phase. It does not describe output shape, size, pagination, or access requirements, so the added behavioral context is moderate.

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, front-loaded with the action and then the three phases. The final 'Summarizes the three pipeline stages' is mildly redundant but the description remains 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?

For a simple read-only tool with one parameter and no output schema, the description covers the three return categories an agent needs to know. It still omits parameter detail and output format, but the core completeness is adequate.

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 0% and the sole parameter experiment_id has no description in the schema. The description only implies 'for an experiment' and does not specify the identifier's format or meaning, so it fails to compensate for the coverage gap.

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 a specific verb and resource ('Get the pipeline-stage provenance trail for an experiment') and enumerates the three returned components, so the tool's purpose is clear. It does not name sibling tools such as get_experiment_results or get_experiment_logs to differentiate its role, so 4 rather than 5.

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 establishes the experiment context but gives no explicit when-to-use or when-not-to-use guidance versus get_experiment_results, get_experiment_logs, or get_dataset. Only implied usage is present.

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