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mlb_editorial_feed

Fetch paginated MLB.com editorial feeds for news, video, or selections by slug. Discover slugs with mlb-search and mlb-discovery.

Instructions

Get an MLB.com editorial feed. Returns a paginated first-party MLB.com news, video, or selection feed. Slugs are dynamic and not a complete closed topic catalog; discover current topic suggestions with mlb-search and sections with mlb-discovery. Feed items retain upstream Article, ShortContent, VSMContent, or Video fields.

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": {
      "slug": "<slug>"
    },
    "name": "mlb_editorial_feed"
  }
}

Input Schema

Name	Required	Description
`skip`	No	Number of items to skip (0-100000)
`slug`	Yes	MLB feed or selection slug, such as mlb-news-list or sel-vvc-mlb-stories
`limit`	No	Items per page (1-100)
`language`	No	Feed locale

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.17.7Oct 1, 2026

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 behavioral burden and does well: it discloses pagination, first-party sourcing, dynamic slug behavior, and that feed items retain upstream Article/ShortContent/VSMContent/Video fields. It does not mention authentication, rate limits, or response consistency, but the coverage is above average for an unannotated read tool.

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

Conciseness4/5

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

Four sentences, front-loaded with purpose and return details, then routing guidance, then a note on retained fields. No filler, though the last sentence about upstream fields could be merged into the second for tighter structure.

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

Completeness4/5

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

Given 4 parameters, no output schema, and no annotations, the description covers purpose, pagination, slug discovery, and return content types. It is nearly complete, missing only minor operational details like auth or rate limits.

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

Parameters4/5

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

Schema coverage is 100% so the baseline is 3, but the description adds valuable context for the slug parameter: it is dynamic, not a closed catalog, and can be discovered via mlb-search and mlb-discovery. This meaning goes beyond the schema's example values.

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 ('Get') and resource ('MLB.com editorial feed'), then clarifies the return types (news, video, selection feed) and explicitly distinguishes itself from siblings mlb-search and mlb-discovery. An agent can tell what this tool does and is not.

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 routes the agent to alternatives for slug discovery: 'discover current topic suggestions with mlb-search and sections with mlb-discovery.' It also warns that slugs are dynamic and not a closed catalog, which is a clear usage condition.

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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