{"uid":"cap_YkZ9G4ICJqFkERtKLHyMs","slug":"text-keywords-299c288e","name":"text-keywords","description":"Keyword extraction from text: the top terms and bigrams by frequency with stopwords removed. Tag, route or index agent-generated content. $0.01 per call.","url":"https://intel.rallylive.ca/data/keywords-text","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET"],"type":"string"},"queryParams":{"type":"object","properties":{}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_IPij739oKHjnEzPnUt-zQ","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts the top keywords and bigrams from a block of text by frequency with stopwords removed, for tagging, routing, or indexing content.","exampleAgentPrompt":"Pull the top keywords and bigrams from this article text so I can tag and index it: 'Artificial intelligence is transforming healthcare by enabling faster diagnostics and personalized treatment plans across major hospital networks.'","exampleUseCases":[{"title":"Auto-tagging agent-generated blog posts","prompt":"Extract the top keywords and bigrams from this blog post so I can automatically assign tags before publishing: 'Cloud computing adoption continues to surge among enterprise firms, with multi-cloud strategies becoming the dominant approach for resilience and cost control.'"},{"title":"Routing customer support tickets by topic","prompt":"Get me the key terms from this support message so I can route it to the right team: 'My payment failed twice and I still see a charge on my credit card — I need a refund urgently.'"},{"title":"Indexing research summaries for search","prompt":"Extract the most frequent keywords and two-word phrases from this research abstract so I can index it properly in our knowledge base: 'Quantum entanglement enables instantaneous correlation between particles regardless of distance, forming the basis for quantum cryptography and secure communication protocols.'"}],"resultDescription":"Returns the top keywords (single terms) and bigrams (two-word phrases) ranked by frequency after stopword removal, enabling downstream tagging, content routing, or search indexing of the input text.","failureModes":["Empty or missing input text returns an error or empty keyword list","Very short input (1-2 words) may yield no meaningful bigrams","Non-English text may produce poor results if stopwords are English-only","Highly repetitive or boilerplate text may surface low-value terms","Network or payment authorization failure returns a 402 or 5xx error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, fast keyword and bigram extraction from free-form text for tagging, routing, or indexing purposes, especially in agentic pipelines where content must be classified or indexed on the fly. It is ideal for English-language text analysis where full NLP pipelines are overkill and stopword-filtered frequency counts are sufficient. Prefer alternatives when you need sentiment analysis, entity recognition, semantic embeddings, or multi-language support.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T13:13:40.894Z","isFirstParty":false}