l2kc_recommend_backend

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

No annotations are provided, so the description carries the full burden. It does useful work by disclosing that mock data are test fixtures, explaining premium GPU preconditions, Colab timeout/CCU budgeting, and that account pinning does not rotate on quota. It still lacks broader behavioral details such as permissions or side effects, but covers the domain-specific behavior well.

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 compact and front-loads the core action. Each sentence carries a domain rule, though some phrasing is terse enough to feel cryptic, such as 'A premium GPU needs scheduler.allow_premium_gpu plus allow_premium.'

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?

The tool has 8 parameters with 0% schema description coverage and no annotations, and an output schema exists so return values need not be described. The description covers key behavior and some parameters, but half the parameters lack any explanatory context, leaving notable gaps for an agent to call it confidently.

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%, so the description must compensate for all 8 parameters. It adds meaningful semantics for provider, account, allow_premium, and timeout_seconds, but leaves gpu_type, gpu_count, high_mem, and min_gpu_memory_gb_per_gpu unexplained except for a brief note about per-GPU memory not being summed.

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 first sentence clearly states the action and resource: recommend a backend without submitting. It differentiates from the submit-job sibling by saying 'without submitting', though it does not name that sibling 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?

The phrase 'without submitting' implies this is a pre-flight/dry-run step before gpu_submit_job, but there is no explicit when-to-use/when-not-to-use guidance or named alternative. The domain rules are usage hints, not routing guidance.

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