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list_problem_solutions

Lists community solution articles for a LeetCode problem, returning topic IDs and metadata only; use get_problem_solution with the topicId to read full content.

Instructions

Lists community solution articles for a problem (read-only, no auth). Returns metadata only (topicId)—not full content. Use get_problem_solution with the returned topicId to read the full article. Do not call this when you already have a topicId and need the solution text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoSolutions to skip for pagination (default: 0)
limitNoMax solutions per page (default: 10)
orderByNoSort order: 'HOT' (default), 'MOST_VOTES', or 'MOST_RECENT'HOT
tagSlugsNoFilter by language or algorithm tags, e.g. ['python', 'dynamic-programming']
userInputNoKeyword filter on solution title, content, or author (case-insensitive)
questionSlugYesProblem URL slug (e.g., 'two-sum')—same as in /problems/{slug}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses read-only, no-auth, and that only metadata (topicId) is returned rather than article text. It stops short of describing pagination behavior despite skip/limit params, but the core behavioral profile is covered.

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?

Three tight sentences, front-loaded with the scope and return-shape caveat before the alternative and the exclusion. No filler whatsoever.

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

Completeness5/5

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

With no output schema, the description compensates by explaining exactly what comes back (metadata with topicId, not content) and the follow-up call. Everything an agent needs to invoke it correctly is present.

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

Parameters3/5

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

Schema description coverage is 100%, so all six parameters are self-documented with defaults and examples. The description adds no syntax or format detail beyond the schema, which is the baseline 3 case when the schema does the heavy lifting.

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?

States a specific verb and resource ('Lists community solution articles for a problem') and immediately bounds the scope ('Returns metadata only (topicId)—not full content'). An agent can distinguish it from get_problem_solution without opening either schema.

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

Usage Guidelines5/5

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

Explicitly names the alternative (get_problem_solution) with the returned topicId, and gives a clear when-not rule: 'Do not call this when you already have a topicId and need the solution text.' Routing is unambiguous.

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