digital_sum_sequence

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 describes the iterative process but does not specify output format (e.g., list of integers), handling of edge cases (e.g., negative or zero input), or performance characteristics (e.g., iteration limits). This leaves gaps for a tool with one parameter and no output schema.

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, with the core purpose stated first in a single sentence. The additional domain and category information is brief and relevant. There is no unnecessary verbosity, making it efficient, though slightly more detail could improve completeness.

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 lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It explains the process but misses key details: parameter meaning, output format, error handling, and differentiation from siblings. For a tool with one parameter and iterative behavior, more context is needed to ensure correct usage.

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?

The input schema has 0% description coverage, with one parameter 'n' of type integer. The description does not explain what 'n' represents (e.g., starting number), its valid range, or constraints (e.g., must be positive). This fails to compensate for the lack of schema documentation, leaving the parameter's meaning unclear.

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 sequence by repeatedly applying digital sum until single digit.' It specifies the verb ('generate sequence'), the method ('repeatedly applying digital sum'), and the termination condition ('until single digit'). However, it does not explicitly differentiate from sibling tools like 'digital_root' or 'digital_persistence', which are related but distinct concepts, preventing a perfect score.

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 minimal usage guidance. It mentions the domain ('arithmetic') and category ('iterative_sequences'), which gives some context, but does not specify when to use this tool versus alternatives like 'digital_root' (which computes a single value) or 'digital_persistence' (which counts iterations). No explicit when/when-not instructions or prerequisites are provided.

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