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Crawlora MCP

Crawlora MCP

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rawstory_headlines

Fetch up to 30 Raw Story section headlines by slug, returning titles, URLs, lead summaries, publication times, authors, and images.

Instructions

Get Raw Story section headlines. Returns the latest Raw Story stories, up to 30, for one section hub. section is required and takes one of 15 slugs such as us-news, trump-news, world, commentary or supreme-court. Each item has its title, URL, lead-paragraph summary, publication time, author and image when given. The dormant presidential-campaign-issues hub returns 9 stories.

Input Schema

NameRequiredDescriptionDefault
sectionYesRaw Story section slug

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does meaningful work: it discloses the 30-story cap, the item fields returned (title, URL, summary, publication time, author, image), and the edge case that the dormant 'presidential-campaign-issues' hub yields only 9 stories. It omits any note on auth, rate limits, or freshness semantics, but for a read-only news fetch this is solid behavioral context.

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 the action and resource before the parameter and return details. Every sentence carries information (scope, param constraint, return shape, edge case), with only minor redundancy between the prose slug examples and the schema enum.

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?

No output schema exists, so the description must describe returns, and it does so by listing the per-item fields. Combined with the parameter explanation and the dormant-hub caveat, an agent has what it needs to call the tool correctly; only the absence of any sibling routing guidance keeps it short of a 5.

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% and the enum already lists all 15 slugs, so the baseline would be 3. The description adds value by explaining what the parameter means semantically (a 'section hub'), confirming it is required, and giving example slugs such as us-news, trump-news and supreme-court, which helps an agent pick a valid value.

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 and resource: 'Get Raw Story section headlines' and clarifies it returns 'the latest Raw Story stories ... for one section hub.' That is clear enough to distinguish the scope from a generic news feed, though it never names the sibling tools (rawstory_news, rawstory_sections) that an agent would otherwise confuse it with.

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

Usage Guidelines3/5

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

It establishes that 'section' is required and enumerates the slug space, so the invocation condition is implied (use when you want headlines for a named section hub). However, there is no explicit when-to-use-this-vs-alternatives guidance against rawstory_news or rawstory_sections, and no exclusions are given.

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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