toggle_habit_entry

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

With no annotations, the description carries the burden, and it clearly discloses that the operation mutates state and is a two-way toggle: it can remove an existing completion or create one. This is the key behavioral trait an agent needs; it doesn't cover success/failure or authorization, but for a simple toggle that is not essential.

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 short sentences, with the verb and resource first and the conditional outcomes second. No filler or redundancy.

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 low-complexity, 2-parameter tool with a fully described schema, the description captures the tool's purpose and state-dependent behavior. It is slightly thin on when to use vs. alternatives, but nothing essential is missing for invoking it correctly.

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 the schema already documents date format and habitId. The description adds no parameter-level meaning beyond that, which meets the baseline for well-covered schemas.

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 names a specific verb ('toggle'), a resource ('habit completion'), and a date scope, and explains both outcomes. This clearly distinguishes it from sibling tools like update_habit and get_habit_analytics.

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 effect logic ('If already completed... if not completed...') implies when to call and what state it applies to, but it never explicitly tells the agent when to choose this over other habit tools or mentions any prerequisites or exclusions.

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