tag_steps

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

The description notes that output can be large without tags, but does not disclose other behavioral traits like performance or side effects. With no annotations, it carries a moderate burden but still lacks detail.

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 main purpose, no extraneous words. Every sentence contributes meaning.

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 the presence of an output schema, the description is sufficient for understanding purpose and usage. Could mention prerequisites (e.g., event file existence) but overall complete for a simple tool.

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?

Input schema already describes both parameters with 100% coverage. The description adds value by explaining why the 'tags' parameter is important (avoid large output), going beyond schema details.

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 the action ('Get the steps') and resource ('each specified tag from a TensorBoard event file'). It distinguishes from sibling tools like list_tags (which lists tags) and tag_stats (which gives statistics).

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?

Provides guidance on using the 'tags' parameter to avoid large output, implying when it's beneficial to specify tags. Does not explicitly discuss alternatives but clearly differentiates from sibling tools.

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