daily_questionToday's daily coding challenge.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| activeDailyCodingChallengeQuestion | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "activeDailyCodingChallengeQuestion": {
+ "properties": {
+ "date": {
+ "description": "Challenge date",
+ "type": "string"
+ },
+ "link": {
+ "description": "Link to the problem",
+ "type": "string"
+ },
+ "question": {
+ "properties": {
+ "difficulty": {
+ "description": "Difficulty level",
+ "type": "string"
+ },
+ "questionId": {
+ "description": "Problem ID",
+ "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"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond the annotations. Annotations already indicate readOnly=true, idempotent=true. The description merely says 'today's' implying time-dependence but without detail on time zone or caching policy.
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 extremely concise at 4 words, no fluff. It front-loads the core purpose effectively for a simple parameterless tool.
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 the presence of an output schema and rich annotations, the description is minimally complete. However, it does not explain what constitutes a 'daily challenge' or the format, which could be inferred from the schema but is not explicitly stated.
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?
The tool has no parameters and schema coverage is 100%. The description does not need to elaborate on parameters, so it is adequate.
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 states it provides 'Today's daily coding challenge,' specifying verb (challenge) and resource (daily coding). However, it does not differentiate from sibling tools like 'problem' or 'suggest_questions' that may also relate to coding challenges.
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?
No guidance is given on when to use this tool versus siblings. For instance, if the agent needs a specific problem by ID, 'problem' would be more appropriate; but the description does not mention such alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.