get_progress

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

With no annotations provided, the description carries the full burden. It discloses how to interpret the output: 'silent_for_s is the telling number: it stays small while the job advances, and only a large and growing one means something is actually wrong.' It also explains expected behaviors like model loading producing no steps for a minute, showing up as 'working'. This is exemplary transparency beyond a simple operation description.

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 well-structured, starting with a succinct summary, followed by essential context and an args explanation. Every sentence adds value—no fluff. While it is longer than minimal, the additional details (e.g., 'silent_for_s', cost of interrupting) directly support correct usage, making it appropriately sized for the tool's complexity.

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 tool has only one optional parameter and no annotations, the description fully covers the parameter semantics, output interpretation, and behavioral context. It explains what is reported (step, percent, elapsed time, ETA), how to interpret silent_for_s, and why waiting is preferable to interrupting. No critical information is missing.

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?

The input schema only defines prompt_id as a string with a default. The description compensates fully with an Args section: 'prompt_id: which run to report on. Defaults to the most recent one.' This clarifies the exact meaning and default behavior, going significantly beyond the schema. Since schema description coverage is 0%, this compensation is essential and well-executed.

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 tool's purpose: 'Report how far a run has got: step, percent, elapsed time and an ETA.' It uses a specific verb ('report') and resource ('a run'), and distinguishes itself from sibling tools like get_download_progress and get_result by focusing on run progress.

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 gives strong guidance on when to use the tool: 'A generation takes minutes... check here instead of guessing.' It also advises against interrupting and re-running: 'Interrupting and re-running costs more than waiting.' While it doesn't explicitly name alternative tools, it provides clear contextual direction.

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