Skip to main content
Glama

Problem

problem
Read-onlyIdempotent

Problem detail by slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
title_slugYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "title_slug": "two-sum"
      +  },
      +  {
      +    "title_slug": "longest-substring-without-repeating-characters"
      +  }
      +]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "question": {
      +      "properties": {
      +        "content": {
      +          "description": "Problem description",
      +          "type": "string"
      +        },
      +        "difficulty": {
      +          "description": "Difficulty level",
      +          "type": "string"
      +        },
      +        "dislikes": {
      +          "description": "Number of dislikes",
      +          "type": "number"
      +        },
      +        "isPaidOnly": {
      +          "description": "Whether problem is premium",
      +          "type": "boolean"
      +        },
      +        "likes": {
      +          "description": "Number of likes",
      +          "type": "number"
      +        },
      +        "questionId": {
      +          "description": "Problem ID",
      +          "type": "string"
      +        },
      +        "stats": {
      +          "description": "Problem statistics",
      +          "type": "string"
      +        },
      +        "title": {
      +          "description": "Problem title",
      +          "type": "string"
      +        },
      +        "titleSlug": {
      +          "description": "Problem title slug",
      +          "type": "string"
      +        },
      +        "topicTags": {
      +          "description": "Topic tags",
      +          "items": {
      +            "properties": {
      +              "name": {
      +                "description": "Tag name",
      +                "type": "string"
      +              },
      +              "slug": {
      +                "description": "Tag slug",
      +                "type": "string"
      +              }
      +            },
      +            "type": "object"
      +          },
      +          "type": "array"
      +        }
      +      },
      +      "type": "object"
      +    }
      +  },
      +  "type": "object"
      +}
  2. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and behavior. The description adds no extra context (e.g., authentication, rate limits, caching), so it is adequate but not additive.

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

Conciseness3/5

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

The description is extremely concise (5 words) and front-loaded, but it sacrifices necessary detail. It is not 'appropriately sized' because it omits information about what the tool returns or how the slug is used.

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

Completeness2/5

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

Given the tool has 1 parameter, annotations, and an output schema, the description is too brief. It does not specify what 'detail' includes (e.g., problem statement, constraints, examples), leaving the agent uninformed about the output.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain parameters. It implies 'title_slug' is the slug but does not clarify format, validation rules, or examples beyond the schema's examples. This fails to compensate for the missing schema descriptions.

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

Purpose4/5

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

The description 'Problem detail by slug.' clearly states the action (retrieve details) and resource (problem) using a specific identifier (slug). It distinguishes from siblings like 'problemset_stats' or 'daily_question' which serve different purposes.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives such as 'problemset_stats' or 'user_recent_submissions'. The agent receives no context about tool selection criteria.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.1/5.0
Disambiguation2/5

Multiple tools have overlapping roles: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve the same lookup purpose, and there are six different Polymarket tools with similar names and functions. The inclusion of a large unrelated data platform alongside a few LeetCode tools makes selection additionally confusing.

Naming Consistency4/5

Almost all tools follow a consistent snake_case verb_noun pattern (ask_pipeworx, compare_entities, list_subscriptions, etc.). Minor exceptions like 'problem' and 'daily_question' are still readable and don't break the overall predictability.

Tool Count2/5

37 tools is far too many for a server named 'Leetcode' — the vast majority are unrelated Pipeworx data, prediction-market, and memory tools. Even as a general data server the count is heavy, and for the apparent LeetCode purpose it is severely over-scoped.

Completeness2/5

The LeetCode-specific tools cover basic user stats and problem details but lack problem listing/search, submissions, or any interaction beyond read-only queries. The Pipeworx side is extensive but irrelevant to the server's stated purpose, so the core domain has significant gaps.