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

With no annotations, the description carries the full behavioral burden. It does disclose the state-dependent return payload (status while running, full results once complete) and what show_misses yields, but it says nothing about read-only safety, whether polling is expected/repeatable, permissions, or error behavior for an unknown job_id.

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?

A single dense sentence that front-loads the primary purpose (job status) before the conditional results. It is efficient, though the long comma-separated enumeration makes it slightly harder to scan than a structured breakdown would be.

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?

There is no output schema and no annotations, so the description must carry the return-value load — and it does so thoroughly, covering status, ranked metrics, misses, and recommendations. Gaps remain around error handling, job-not-found behavior, and result pagination/size for large benchmark runs.

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 coverage is 75% (job_id undocumented), so the schema does most of the work, but the description adds real meaning: it links 'the tests each model missed with its answer' to show_misses and explains that a recommendation is produced for 'the chosen objective' with 'quick picks for the others', clarifying optimize_for's effect on output. Only tolerance goes unmentioned in the description.

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+resource combination ('Status of a benchmark job, and once completed the ranked results') and enumerates the concrete outputs (score, stability, cost per run, latency, missed tests, recommendation). An agent can distinguish this from run_benchmark or estimate_cost, though no sibling is named explicitly.

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?

'Once completed' implies this is the retrieval step following run_benchmark, giving an implied usage context. However, it never states when to use this versus watch_task for progress polling, nor any prerequisite (e.g., that a job_id must come from run_benchmark).

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