recommend_daily_tasks_ai

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

With no annotations, the description carries the full behavioral burden and largely fails it. It discloses the underlying model but says nothing about cost, latency, external API/key requirements, or the fact that this is a non-mutating recommendation read. The fallback behavior is only described in the schema, not the 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?

A single front-loaded sentence with no filler; the engine and the sophistication claim are established immediately. It is efficient, though its brevity contributes to gaps elsewhere rather than being a structural flaw.

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?

For a 2-parameter tool with no output schema, the description covers the core intent but omits what is returned (shape/ordering of recommendations) and any guidance on choosing it over the rule-based sibling. Annotations are absent, so these gaps are not compensated elsewhere.

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 100%, so both parameters (max_tasks, use_ai_reasoning) are already fully documented in the schema with defaults and bounds. The description adds no syntax, format, or constraint detail beyond what the schema provides, so the baseline 3 applies.

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?

States a specific verb+resource ('recommend daily tasks') and names the engine ('DeepSeek'), with an implicit contrast to the rule-based sibling. It does not name the sibling tool explicitly, so an agent must infer that recommend_daily_tasks is the rule-based counterpart.

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 parenthetical 'more sophisticated than rule-based' implies this is the preferred/heavier option, but there is no explicit when-to-use or when-not-to-use guidance relative to recommend_daily_tasks. Usage is inferable from the sibling name and the use_ai_reasoning parameter, but not stated.

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