get_practiceproblems

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

The description discloses the analysis and recommendation behavior, including the rating constraint (+300). However, with no annotations provided, it carries full burden. It lacks details on authentication needs, error handling (e.g., no solved problems), potential side effects (none expected), or output format. It is adequate but not fully transparent.

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 sentences: first describes the core analysis, second specifies the output and constraint. No wasted words, front-loaded with purpose. Very concise and well-structured.

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 a simple input schema (one param, no annotations) and an output schema (though not shown), the description is largely complete: it explains what the tool does, the input's role, and the output's nature. It does not address edge cases (e.g., no weak topics), but the existence of an output schema reduces that burden. Siblings provide context for alternatives.

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 0% for the single parameter 'username'. The description adds meaning by stating it analyzes 'a user's solved problems', clarifying that username identifies the user. However, it does not describe the username format, constraints, or validate input. It compensates partially, but more detail would improve.

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 specifies 'Analyzes a user's solved problems to identify their weakest topics' and 'Recommends up to 3 practice problems', providing a specific verb (analyze, recommend) and resource (user's problems, practice problems). It distinguishes from siblings like get_random_practice (random) and get_problemlist (list) by focusing on weak topics and a rating range.

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 implies usage for identifying weak topics and getting focused practice, but does not explicitly state when to use this tool over alternatives (e.g., get_random_practice for random problems) or mention any prerequisites (e.g., user must have solved problems). No exclusions or when-not-to conditions are provided.

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