get_problemlist

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

With no annotations, the description carries the burden. It explains that results are a list of up to 10 problems with specific fields, and details the filtering parameters. It does not mention rate limits or authentication, but for a read-like search, this is sufficient.

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: a one-sentence overview followed by a bullet list of parameters. Every sentence is informative, and the structure makes it easy to parse.

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 tool with 5 parameters and an output schema, the description covers all input parameters and describes the return format (10 problems with names, ratings, tags, links), making it complete for an agent to invoke 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 description coverage is 0%, so description must compensate. It provides clear explanations for all 5 parameters with examples (e.g., 'min_rating: Minimum difficulty rating (e.g., 800)'), adding critical meaning absent from the schema.

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 starts with a specific action ('Search') and resource ('Codeforces problemset'), and specifies an output limit of 10 problems. It clearly distinguishes from siblings like get_practiceproblems or get_random_practice by focusing on filtered search.

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 clearly states what the tool does but does not explicitly guide when to use it over siblings. However, the purpose is specific enough that an agent can infer appropriate usage contexts.

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