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Pure Report — Neutral News

Compare outlet framing

compare_coverage
Read-only

Show how outlets across the political spectrum framed one event: a per-outlet bias-score spectrum and, where they editorialized, the verbatim framing quotes grouped by left/center/right. The core 'compare the coverage' view — use it to detect slant and consensus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesEvent slug from trending_events or a search_news result.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
nameNo
slugYes
framing_spectrumNo
how_each_side_framed_itNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "framing_spectrum": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "how_each_side_framed_it": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "name": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "slug": {
      +      "type": "string"
      +    },
      +    "url": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "slug",
      +    "url"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already set readOnlyHint=true, so the description's mention of output details (bias-score spectrum, quotes) adds useful context without contradicting. It doesn't add behavioral traits beyond what annotations provide, but the output description is valuable.

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?

Two sentences deliver the purpose and usage efficiently. No fluff, front-loaded with key action and output.

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

Completeness5/5

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

The description fully covers the tool's complexity: it explains the output (spectrum, framing quotes grouped by bias) and its role as the core comparison view. With an output schema present, return values need no extra explanation.

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% with a clear description of the slug parameter. The description adds context that the slug comes from trending_events or search_news, providing extra meaning beyond the schema.

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?

The description clearly states the tool shows how outlets framed an event with a bias-score spectrum and verbatim framing quotes grouped by ideology. It distinguishes itself from siblings like get_article (single article) and trending_events (list of events).

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

Usage Guidelines4/5

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

It tells agents to use it to detect slant and consensus, and mentions the slug comes from trending_events or search_news. However, it could explicitly state when not to use it or list alternatives (e.g., use get_article for a single article).

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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