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analyze_leetcode

Analyze a student's public LeetCode profile to extract solved problems and topic distribution, enabling skill-based placement evaluation.

Instructions

Analyze a student's public LeetCode profile.

Args:
    student_id: The student's UUID.

Returns:
    LeetCode analysis including problems solved and topic distribution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
student_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It notes 'public LeetCode profile,' implying read-only access without authentication, and lists the return content. However, it does not disclose error handling, rate limits, or what happens if the profile is missing—common behavioral context. This is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, with a clear one-sentence purpose followed by an Args/Returns structure. Every word adds value, and there is no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists, the description does not need to detail return values, and it provides the essential behavioral context (public profile, key output topics). It is complete for a low-complexity tool with one parameter, though it could mention error cases or prerequisites. Overall, sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only provides the parameter name and type (string), but the description adds 'The student's UUID,' clarifying the expected format and meaning. With 0% schema description coverage, this compensation is valuable and earns a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb and resource: 'Analyze a student's public LeetCode profile.' It distinguishes itself from siblings like analyze_github and analyze_resume by explicitly focusing on LeetCode, and the mention of output (problems solved, topic distribution) further clarifies its scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The context of use is clear: for analyzing a student's LeetCode profile. No explicit alternatives or when-not-to-use guidelines are provided, but the description implies the appropriate scenario. Since the siblings include other analysis tools, the absence of explicit alternatives prevents a 5, but the clarity merits a 4.

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

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