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gdelt_tv_wordcloud

Generate a frequency-ranked word cloud from US TV news coverage by station and channel to reveal dominant words in transcripts, captions, concepts, onscreen text, or visuals.

Instructions

Word cloud for US television news coverage. Returns a frequency-ranked word cloud for US television coverage. channel is required and picks what is counted: transcript, caption, concept, onscreen_text or visual; station is also required. Match with the same channel options (with exclude_ counterparts) and limit by show, day_of_week, timespan or from and to. Each word has a label and count.

Input Schema

NameRequiredDescriptionDefault
toNoEnd of an absolute time window. Same formats as from.
fromNoStart of an absolute time window. Accepts YYYY-MM-DD, RFC3339, or GDELT's raw YYYYMMDDHHMMSS. Cannot be combined with timespan.
showNoLimit to an exact show name.
visualNoSearch visual object/activity labels from computer vision (GDELT's visual: operator). Repeatable; multiple values are OR'd together.
captionNoSearch human-provided closed captioning (GDELT's cap: operator). Repeatable; multiple values are OR'd together.
channelYesRequired. Which match channel to build a word cloud from.
conceptNoSearch Google Knowledge Graph concepts extracted from captioning, by MID code (GDELT's capnlp: operator). Repeatable; multiple values are OR'd together.
stationYesRequired. Station to search.
timespanNoRelative time window ending now, e.g. 1h, 7d, 3m, 1y. Cannot be combined with from/to. GDELT's TV archive starts July 6, 2010.
transcriptNoSearch machine-generated speech-to-text transcripts (GDELT's asr: operator). Repeatable; multiple values are OR'd together. Short phrases only (GDELT caps each at 5 words).
day_of_weekNoLimit to a day of week, 0 (Sunday) through 7 (Saturday), PST.
onscreen_textNoSearch OCR'd onscreen text/chyrons (GDELT's ocr: operator). Repeatable; multiple values are OR'd together. Short phrases only (GDELT caps each at 5 words).
exclude_visualNoExclude clips whose visual labels match this value (GDELT's -visual: operator). Repeatable; every value must be absent.
exclude_captionNoExclude clips whose closed captioning matches this value (GDELT's -cap: operator). Repeatable; every value must be absent.
exclude_conceptNoExclude clips whose extracted concepts match this MID code (GDELT's -capnlp: operator). Repeatable; every value must be absent.
exclude_transcriptNoExclude clips whose speech-to-text transcript matches this value (GDELT's -asr: operator). Repeatable; every value must be absent.
exclude_onscreen_textNoExclude clips whose OCR'd onscreen text matches this value (GDELT's -ocr: operator). Repeatable; every value must be absent.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed12 schema fields changedv1.17.5
    • addedInput schema / properties / caption / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / channel / enum
      Added value: +[
      +  "transcript",
      +  "caption",
      +  "concept",
      +  "onscreen_text",
      +  "visual"
      +]
    • addedInput schema / properties / concept / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / exclude_caption / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / exclude_concept / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / exclude_onscreen_text / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / exclude_transcript / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / exclude_visual / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / onscreen_text / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / station / enum
      Added value: +[
      +  "CNN",
      +  "MSNBC",
      +  "FOXNEWS",
      +  "BBCNEWS",
      +  "KGO",
      +  "KPIX",
      +  "KNTV"
      +]
    • addedInput schema / properties / transcript / items
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / visual / items
      Added value: +{
      +  "type": "string"
      +}
  2. Addedv1.16.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return shape ('Each word has a label and count') and the filter semantics (match with exclude_ counterparts, limit by show/day_of_week/timespan/from/to), which is useful. It does not mention permissions, rate limits, or explicitly confirm read-only/no side effects.

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

Conciseness3/5

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

The first two sentences are redundant, both restating that this is a frequency-ranked word cloud of US television coverage. The rest is dense but front-loads the required parameters reasonably; the duplication is wasted space.

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?

There is no output schema, and the description compensates by stating the return fields (label, count). For a 17-parameter tool with no annotations it is adequate but thin: defaults, time-window behavior, and the meaning of unstated filters are left to the schema.

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 description coverage is 100%, so the baseline is 3. The description adds a little meaning by stating that `channel` 'picks what is counted' and noting the exclude_ counterparts, but most parameter semantics (formats, enums, time windows) are already fully documented in the schema.

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+resource: it produces a frequency-ranked word cloud of US television news coverage, which is a distinct artifact from sibling timeline/search/chart tools. However, it never names or contrasts against siblings like gdelt_tv_timeline or gdelt_tv_stationchart, leaving differentiation to the agent's inference.

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 explains that `channel` is required and controls what is counted, and that `station` is also required, which implies the usage context. But there is no explicit when-to-use versus alternatives and no exclusions, so an agent must infer when a word cloud is preferable to a timeline or chart.

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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