{"uid":"cap_Po6u0sltBL13elzx_C9aI","slug":"whatchuneed-llm-code-review-7b364bd8","name":"whatchuneed LLM Code Review","description":"320+ pay-per-call API endpoints across accommodation, LLM, code execution, crypto, medical, finance, and more. One API, one payment. Powered by x402 protocol.","url":"https://whatchuneed.vercel.app/api/llm/code","method":"POST","headers":{},"bodySchema":{"type":"object","required":["code"],"properties":{"code":{"type":"string"},"task":{"type":"string"},"language":{"type":"string"}}},"responseSchema":{"type":"object","properties":{"issues":{"type":"array","items":{"type":"object","properties":{"line":{"type":"integer"},"message":{"type":"string"},"severity":{"type":"string"}}}},"review":{"type":"string"},"suggestions":{"type":"array","items":{"type":"string"}}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.1","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":"$0.1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_dX_gKm7RTGwbmBYxtcUAG","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.1","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes submitted source code and returns a structured review with issues, severities, and improvement suggestions","exampleAgentPrompt":"Can you review this Python function for me and flag any bugs, bad practices, or places I could improve it? The task is to parse a CSV file and return a list of dicts.","exampleUseCases":[{"title":"Bug detection in production code","prompt":"I just wrote this JavaScript async function that fetches data and handles errors — can you review it, flag any issues by line number, and tell me how severe each problem is?"},{"title":"Code quality check before PR","prompt":"Before I submit this pull request, can you review my Python database connection code and give me a list of suggestions to improve it? I want to catch anything that might cause issues in production."},{"title":"Learning from code feedback","prompt":"I'm learning Go and wrote this HTTP handler — can you review it and explain what issues it has and how I could write it better?"}],"resultDescription":"Returns a structured object containing: an array of issues (each with line number, message, and severity), a prose review summary, and an array of actionable suggestion strings for improving the code.","failureModes":["Missing required 'code' field returns validation error","Very large code submissions may time out or be truncated","Unsupported or ambiguous language may produce generic or inaccurate feedback","Payment failure via x402 protocol returns 402 status with no result","Malformed JSON body returns 400 error"],"whenToPreferThis":"Choose this endpoint when you need a structured, machine-readable code review with per-line issue tracking and severity ratings — especially useful for automated CI pipelines, agent-driven development workflows, or when you need programmatic access to code quality feedback. Prefer this over general LLM chat for code because the output is schema-structured with explicit issues array and line numbers rather than free-form prose.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T13:04:33.891Z","isFirstParty":false}