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dots-mcp

dots-mcp

by mergisi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

search_dots_resources

Search the awesome-dots index for OpenAI Dots guides, news, tools, and use cases by keyword to find relevant resources.

Instructions

Search the awesome-dots list for OpenAI Dots guides, news, tools and use cases by keyword.

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_dots_resources"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesKeyword(s) to search in names, descriptions and sections

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a read-only keyword search but says nothing about result format, ranking, pagination, or scope limits, leaving the agent to assume behavior.

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 that states the verb, target corpus, content types, and search mode with no filler. Every phrase contributes to identifying the tool.

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

Completeness3/5

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

For a simple one-parameter search tool with no output schema and no annotations, the description covers the essential purpose but omits sibling differentiation and any behavioral details such as result ordering. Adequate but with clear gaps.

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 coverage is 100%, so the single 'query' parameter is already well documented in the schema. The description adds only that matching is 'by keyword,' which does not meaningfully extend the schema's explanation, so the baseline of 3 for high coverage applies.

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 states a specific verb ('Search') and resource ('the awesome-dots list for OpenAI Dots guides, news, tools and use cases'), making the tool easy to identify. It does not, however, explicitly contrast itself with the sibling list_dots_resources, leaving sibling differentiation to inference.

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?

The phrase 'by keyword' hints at when the tool is appropriate, but there is no explicit guidance on when to use it versus list_dots_resources, nor any exclusions or prerequisites. The agent must infer the search-vs-list distinction on its own.

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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