generate_proposal

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions AI generation and the output structure but lacks details on permissions, rate limits, error handling, or whether the proposal is saved or editable. For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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 concise and front-loaded, stating the main purpose in the first sentence and listing key components in the second. Both sentences earn their place by clarifying the tool's function and output structure without unnecessary details, though it could be slightly more structured for readability.

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 no annotations, no output schema, and 6 parameters with full schema coverage, the description is moderately complete. It covers the tool's purpose and output components but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for an AI agent to fully understand when and how to invoke it effectively.

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 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond the schema, such as explaining how parameters interact or providing usage examples. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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: 'Generate a professional freelance project proposal using AI' with specific components listed (executive summary, scope of work, timeline, pricing, and terms). It uses a specific verb ('Generate') and resource ('freelance project proposal'), though without sibling tools, differentiation isn't applicable. The description avoids tautology by elaborating beyond the name.

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 provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It simply states what the tool does without context for its application, such as when it's appropriate for freelance work versus other proposal types or what scenarios it best fits.

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