{"uid":"cap_lGyO56f1JRjtzGHQUYfG9","slug":"agenttools-token-estimator-3b471869","name":"AgentTools Token Estimator","description":"Estimate how many tokens a text consumes for each major model family (GPT, Claude, Gemini, Llama, DeepSeek) using a character/word heuristic that is within ~10% of real BPE tokenizers — enough for context budgeting and cost math, with zero dependencies. Use this when an agent needs to approximate token counts per LLM family, ±10%.","url":"https://agentstoolshub.com/api/v1/dev/token-estimator?utm_source=zero.xyz","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","required":["text"],"properties":{"text":{"type":"string","description":"Text"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","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":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_ARClnchRcieYFdt85_f0t","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Estimates token counts for a given text across major LLM families (GPT, Claude, Gemini, Llama, DeepSeek) using a character/word heuristic accurate to within ~10% of real BPE tokenizers.","exampleAgentPrompt":"How many tokens does this text use across GPT, Claude, Gemini, Llama, and DeepSeek — can you estimate it for me: 'The quick brown fox jumps over the lazy dog. This is a sample sentence for testing purposes.'","exampleUseCases":[{"title":"Context window budget check","prompt":"Before I send this system prompt to Claude, can you estimate how many tokens it will consume so I know how much room I have left in the context window? Here's the text: 'You are a helpful assistant specializing in customer support for a SaaS product. Always respond politely and escalate billing issues to a human agent.'"},{"title":"LLM cost comparison across families","prompt":"I need to know roughly how many tokens this paragraph will use for GPT, Llama, and DeepSeek so I can compare costs before choosing which model to call: 'Quarterly earnings reports showed a 12% increase in revenue driven by strong performance in the APAC region, with operating margins improving by 3 points year-over-year.'"},{"title":"Prompt length validation before batch job","prompt":"Can you check the token count for this template text across all major model families — I want to make sure it stays under 500 tokens for every LLM I'm targeting: 'Dear {{customer_name}}, thank you for your recent purchase of {{product_name}}. Your order will arrive by {{delivery_date}}. Please contact support if you have any questions.'"}],"resultDescription":"Returns estimated token counts for the input text broken down by major LLM model families (GPT, Claude, Gemini, Llama, DeepSeek), computed via a character/word heuristic that approximates real BPE tokenizer output within ±10%. Useful for context budgeting and per-model cost math without needing to run actual tokenizers.","failureModes":["Missing required 'text' query parameter returns an error","Empty string input may return zero counts or an error","Extremely long texts may hit server-side limits","Network timeout on slow connections","Non-UTF-8 or binary content in text field may cause parsing errors"],"whenToPreferThis":"Choose this endpoint when you need a fast, zero-dependency token count estimate across multiple LLM families simultaneously — especially useful for pre-flight context budgeting, cost math, or prompt length validation where ±10% accuracy is sufficient and you don't want to run individual tokenizer libraries per model family.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T12:48:36.304Z","isFirstParty":false,"canonicalSlug":"agenttools-token-estimator-3b471869"}