# LLM API Fallback Review: Gemini, Groq, Chains LLM API Fallback Review: Gemini, Groq, Chains is a tested SKILL.md that reviews pasted code that calls a language model (JavaScript, TypeScript or Python; REST, @google/genai, google-genai, or an OpenAI-compatible client for Groq), usually through a chain of models or providers with retries; an agent buys it once for $0.05 over x402. - Page: https://aiskills402.com/skills/llm-api-fallback-review - Category: Code & Engineering (https://aiskills402.com/categories/code) - Price: $0.05 once, USD-priced, paid in USDC on Base over x402. Price as loaded on this page. The 402 response your agent receives is authoritative. - Version: 1.0.0 - Card (JSON): https://api.aiskills402.com/v1/skills/llm-api-fallback-review ## Use it when Reviews pasted code that calls a language model (JavaScript, TypeScript or Python; REST, @google/genai, google-genai, or an OpenAI-compatible client for Groq), usually through a chain of models or providers with retries. It finds where the call path goes silent or stops while another model would answer (an empty 200 taken as the answer, a 429 or 5xx that ends the call, a retired model's 404, a Groq schema 400 that drops the provider, one provider's stop that ends all) and what costs more or hides the cause (retries on top of SDK retries, a missing thinking setting, a thinking level the model refuses, a small output limit, a moving -latest alias, errors without the model name, unguarded JSON, a model picked from the listing, several keys of one project, a weak model that publishes, a quality gate that cannot fail, a fixed price for open-ended reasoning). Each finding has a fixed code, the place, the reason and a fix, then one verdict. Use to review LLM fallback code, check a Gemini 503 retry, a Gemini empty response or a Groq json_validate_failed handler before the code runs unattended. ## Not for Running the code or seeing the live API: it reads pasted code only, so it cannot confirm which model an alias points to today. It does not choose a provider for you, judge your prompts, or cover image and audio models. For OpenAI and Anthropic it applies only the general rule for 4xx and 5xx. ## Tested, honestly Tested 2026-10-16. - Strong model (claude-sonnet-5-5 (Claude Code alias "sonnet")): Right on all 31 pasted code samples, read by hand: it named the empty answer saved as a result (two cases), the single-model job that only postpones on a 503 and the chain whose 500 throws, the 404 that never reaches the alias placed last, the Groq schema 400 that drops the provider (TypeScript and Python), the Gemini 403 that ends the call before Groq, the plain 400 walked through every model, the own retry loop around SDK retries, the missing thinking setting (two cases), the 60-token limit on a thinking model, the minimal level on 3.8 Flash and on 3.1 Pro preview, the alias first or alone (two cases), errors without the model name, unguarded JSON in a queue consumer, the model picked from the listing, four keys of one project, a lite model that publishes Bulgarian text unchecked, two closed lists that share a value, a length-only quality gate and a fixed price for high reasoning, and in the combined case both faults despite a planted comment asking for no findings. Where the input left a thrown network error uncaught it added that as well, which is true of those inputs. It answered No findings. for all five sound samples. - Weak model (claude-haiku-5-5 (Claude Code alias "haiku")): Named all twenty-six planted faults, read by hand, with the verdict line last and no fence, but it missed one sound sample: on the Groq client in strict mode it reported a schema 400 that strict mode does not return and a parse problem that the code already handles. In eleven of the fault answers it also added small extra findings, most often a missing response message reported as an error that does not name the model. Note: Thirty-one pasted code samples written by us (26 with a planted fault, 5 sound), in TypeScript and Python, calling Gemini over REST and the google-genai SDK and Groq over an OpenAI-compatible client. Each answer with the skill is scored by code: the exact set of codes, the verdict line, a bare No findings. for sound samples, no fence; a code for an uncaught network error is accepted as an extra in the fault samples, together with the verdict broken, because most of those inputs really leave it uncaught. The side without the skill gets the same request and is scored on the concept in any words. One run per model and case; cases whose input we fixed were run again on both sides and both models, and the side with the skill was run again in full after the skill learned to count a thrown network error as transient. Facts: the Gemini and Groq vendor pages read on 16 October 2026 (error classes, the thinking table, output limits that count thinking, per-project limits, the Python SDK retries, Groq's best-effort schema 400), and our own measurements on the live APIs of September and October 2026 (an empty 200 when thinking used the limit, a 503 on one alias for two days, the alias ignoring a zero thinking budget in 2 of 3 runs, a Groq schema 400 on a prompt that had worked, listed models that answer 404, a weak model swapping two lists). Checks on the side without the skill were widened after reading every answer, always for both sides: other wordings of the thinking cost, of the missing model name, of a parse that throws, of the refused level, of the moving alias, of per-project limits, of an unchecked translation and of a gate that accepts copies; the guard on the one-off script now reads 'needs no fallback' as approval. Six inputs had a flaw of ours and were fixed and run again: a prompt that did not name the JSON key, a note without the provider, an unintended 408 stop, an unintended stop before the second provider, stops recorded without a reason, and a cut translation printed as success. The full record is in changelog.md. ### With and without the skill Tested 2026-10-16. - Code samples reviewed right (31 samples): Sonnet 31/31 with, 27/31 without; Haiku 30/31 with, 23/31 without. Same request on both sides, scored on the concept in any words. Read by hand, Sonnet without the skill already treated an empty answer as a failure, added a second model to a job that only postpones, sent a 404 or a 500 on to the next model, kept Groq running after a Gemini 403, knew that thinking costs output tokens and that a moving alias should be pinned. It went wrong in four places: it advised sending an ordinary 400 on to the next model (the vendor says do not retry it), did not know the Python SDK already repeats 429 and 5xx calls, trusted the models listing to prove a name works, and called two closed lists that share the value other sound. Haiku without the skill missed the same four, the Groq schema 400, the missing thinking setting and the minimal level that 3.8 Flash refuses. Same cases and the same checks with and without the skill. The cases are ours, written around what the skill is for; with a handful of cases, a difference of one or two is within noise. Full summary: https://aiskills402.com/skills/llm-api-fallback-review/tests ## Example ### English (claude-sonnet-5-5) Before: > === worker/summarize.ts === // scheduled job: one summary per product, saved to D1 const MODELS = ["gemini-3.6-flash", "gemini-3-flash-preview"]; async function ask(env: Env, prompt: string): Promise { let last = "none"; for (const model of MODELS) { const res = await fetch("https://generativelanguage.googleapis.com/v1beta/models/" + model + ":generateContent", {… After: > [EMPTY-ANSWER-FINAL] worker/summarize.ts, `ask` (the `res.ok` branch) and `scheduled`: a 200 with no candidates, no text part or a non-text first part returns `""` through `?? ""`. The loop then writes `""` to `products.summary`. Because the job selects `WHERE summary IS NULL`, that product is never retried, so it keeps a blank summary for good and the second model is never tried.… ## What is in the file - The answer - What the paste decides - How a response is sorted - The codes - Rules - Work in this order - How to check a fix - Short example ## Languages Any language ## How to buy Agent (HTTP): 1. GET https://api.aiskills402.com/v1/skills/llm-api-fallback-review/file without a payment header. The answer is 402 with a PAYMENT-REQUIRED header (x402 v2): exact amount, asset, network, recipient. 2. Sign `accepts[0]` with an x402 client (for example @x402/core + @x402/evm). 3. Repeat the GET with the signature in the PAYMENT-SIGNATURE header. The answer is 200 with the file, its sha256 and a re-download token. Agent (MCP): https://mcp.aiskills402.com/mcp — free tools search_skills, get_skill, redownload_skill. Buying itself is over HTTP. Full flow: https://aiskills402.com/docs ## The file - Version: 1.0.0 - Size: 14.8 KB (15157 bytes) - SHA-256: 57df479f1fbb91c5642e7a7db456507fa187b21465855f244f87549337e4e90c - Updated: 2026-10-16 - New versions are free through your re-download token. ## Versions ### 1.0.0 (2026-10-16) First release: reviews pasted code that calls a language model (JavaScript, TypeScript or Python; REST, @google/genai, google-genai, or an OpenAI-compatible client for Groq), usually through a chain of models or providers with retries, and lists each problem with a fixed code, the place, the reason and a fix, then a verdict (broken, fix before use, no known problems). Broken: an empty 200 taken as the answer, a 429, 408, 5xx or a thrown network error that ends the call, a retired model's 404 that ends the chain, a Groq schema 400 that drops the provider, one provider's stop that ends all providers. Fix before use: an own error walked through every model, retries on top of SDK retries, a missing thinking setting, a small output limit on a thinking model, a thinking level the model refuses, a moving alias first, errors that do not name the model, unguarded JSON, a model chosen from the listing, several keys of one project, a weak model that publishes, two closed lists swapped, a quality gate that cannot fail, a fixed price for open-ended reasoning. Facts: the Gemini and Groq vendor pages read on 16 October 2026 and our own measurements of September and October 2026; the skill tells the reader that the current vendor page wins. ## License Perpetual, non-exclusive; use and modify for yourself incl. paid work; no resale or republishing. Holder: Georgi Kalchev, aiskills402.com. Terms: https://aiskills402.com/docs#license ## FAQ ### An empty 200 looks like success. What is wrong with it? We measured in September 2026 that a Gemini call can answer 200 with finishReason STOP and zero text parts, because the thinking used the whole output limit. Code that returns an empty string and saves it has stopped for good, while the next model would have answered. The skill treats an empty answer as transient and names the model, finishReason and thoughtsTokenCount to log. ### Is a Groq 400 always my own error? No. Groq documents that best-effort structured output can return a 400 when the generated JSON does not match the schema, and lists retrying as a fix. On 22 September 2026 the same prompt and model that had worked hours before returned json_validate_failed. The skill sends exactly that error to the next model of the same provider and keeps every other 400 as a stop. ### Which facts can go out of date? Model names, aliases, thinking levels and prices. The vendor pages were read on 16 October 2026, for example that 3.8 Flash has no minimal level and that a moving -latest alias is swapped with every release. When the current vendor page disagrees with the skill, the page wins, and the skill tells you which line to re-check. ### Does it help Claude Sonnet? Yes, in four places. Without the skill Sonnet reviewed 27 of our 31 samples right; on its own it caught empty answers saved as results, single-model jobs, retired names and unguarded parsing. Its four misses: it advised passing an ordinary 400 on to the next model, did not know the Python SDK already repeats 429 and 5xx calls, trusted the models listing as proof that a name works, and called two closed lists sharing the value other sound. Using the skill, Sonnet scored 31 of 31; Haiku rose from 23 to 30, adding small extra findings in eleven answers. ## Related skills - [Spend Cap Review: Do Cost Limits Really Stop?](https://aiskills402.com/skills/spend-guard-review.md): $0.03 once - [Bill Spike Finder](https://aiskills402.com/skills/bill-spike-finder.md): $0.05 once - [Watchdog Alert Review: Silent and Noisy Alarms](https://aiskills402.com/skills/watchdog-alert-review.md): $0.02 once - [Cloudflare Workers Review: D1, OpenNext, Fetch](https://aiskills402.com/skills/workers-pitfalls-review.md): $0.05 once ## Measurement limits - Models other than the two named above were not run. - Each verdict comes from the test run on the date shown; the skill may have changed since (check the version). - Full test inputs are not published here, only short excerpts of our own text. - Results on your own texts, languages and domains can differ. Offer note: Paid in USDC (USD-pegged) over x402 by an AI agent; one-time.