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kaggle-context

kaggle-context

by vks-g
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

search_discussions

Search Kaggle competition discussions by keyword to find relevant forum topics and comments. Filter by competition and limit results for targeted research.

Instructions

Keyword search over saved topics and comments, plus titles of other topics.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_discussions"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
competitionNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
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 usefully discloses the search scope (topics, comments, and titles of other topics), which goes beyond the schema, but says nothing about pagination via limit, result ordering, or any access constraints.

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?

A single front-loaded sentence with no wasted words; scope is stated immediately.

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?

For a three-parameter tool with 0% schema description coverage and no annotations, the description is too thin. It omits the competition scoping parameter and the search-vs-list distinction, which an agent needs to invoke it correctly.

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 compensate. It only loosely implies that query is keyword-based and says nothing about the competition filter or the limit parameter, leaving two of three parameters unexplained anywhere.

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?

States a specific verb (keyword search) and resource scope (saved topics, comments, plus titles of other topics), which is clearer than a bare name. It does not, however, distinguish itself from the sibling list_discussions, so an agent still has to infer the search-vs-list boundary.

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?

There is no explicit when-to-use guidance, no exclusions, and no named alternative such as list_discussions. The word 'keyword' weakly implies 'use when you have search terms,' but the choice between searching and listing is left entirely to inference.

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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