benchmark_propose

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

No annotations are provided, so the description carries full burden. It only mentions the core action and rejection condition, but lacks details on side effects, error handling, permissions, or state changes. For a creation tool, more behavioral context is needed.

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 action, and a second sentence adding essential constraints. No wasted words.

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's complexity (nested object with 7 subfields) and no output schema, the description only covers the high-level requirement. It omits explanations of subfields (oracle, qualityScale, comparisonRule) and what constitutes a 'concrete case', making it incomplete for an agent to correctly formulate inputs.

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%. The description adds some meaning by implying the 'benchmarks' array must contain subfields (task-value dimensions, resource dimensions, cases), but it does not explain individual properties like 'name', 'oracle', 'qualityScale', etc. Many parameters remain unclear to an agent.

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 verb ('Propose') and the resource ('benchmark scorecards built from real prior uses/failures'). It includes specific constraints (≥1 task-value dimension, ≥1 resource/cost dimension, ≥1 concrete case) that help differentiate it from sibling tools like benchmark_select or benchmark_run.

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 context for when to use (proposing benchmarks with real prior uses/failures) and includes rejection criteria (hand-waved benchmarks). However, it does not explicitly state when not to use it or mention alternatives like benchmark_select.

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