> ## Documentation Index > Fetch the complete documentation index at: https://docs.fastino.ai/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > Use https://docs.fastino.ai/openapi.json as the source of truth for customer-facing routes. For GLiDE decision inference, call POST https://api.fastino.ai/v1/systemone with model fastino/GLiDE. Do not infer undocumented routes. Read API keys from FASTINO_API_KEY and never embed credentials in code, logs, or reports. # GLiDE primitives and request parameters > The Noul, Choice, and Score primitives behind GLiDE decisions, plus the /v1/systemone request contract and confidence. ## Primitives Every question you ask [GLiDE](/concepts/glide) uses one of three types, sent to `POST /v1/systemone` against a shared `state`: * **[Noul](/concepts/glide-noul)** - a yes/no question that returns a probability between 0 and 1. Think of it as a boolean on a sliding scale. "Does this request qualify for a refund?" might return `0.999` - a 99.9% probability the answer is yes. * **[Choice](/concepts/glide-choice)** - a pick-one-from-many question that returns a probability distribution over up to 255 named options. "Which team should handle this?" might return `{"billing": 0.0006, "returns": 0.999, "shipping": 0.0005}`. * **[Score](/concepts/glide-score)** - a rate-on-a-scale question over an ordered rubric you define. "How urgent is this request?" with three levels might return `score: 0` (low) and `expected_level: 0.276` - a probability-weighted result between low and medium, closer to low. Pick the type that matches the shape of the answer your code needs. Noul vs. Score: a Noul at `0.5` means maximum uncertainty between yes and no - it doesn't express degree. If you need to measure degree (urgency, severity, frustration), use a Score with defined levels. If you need a binary gate, use a Noul. There is no multi-label primitive - each question is single-label. Ask several independent questions in one call if you need several simultaneous judgments; see [Combining multiple questions](#combining-multiple-questions). ## Limits * Each rendered question prompt (`state` plus that question) must fit within **40,000 tokens**. * Choice and Score accept up to **255 options or levels**. * One request evaluates one shared `state`. Put multiple named questions under `questions`; `/v1/systemone` does not accept a batch of independent states. * `usage.input_tokens` sums internal passes across questions, so it can exceed 40,000 even though every individual rendered prompt fits. ## Endpoint | Method | Path | Description | | - | - | - | | `POST` | `/v1/systemone` | Run one or more typed decision questions against a state | See [GLiDE inference](/inference/systemone) for authentication, a complete cURL request, response handling, retries, and errors. ## Request parameters The context to evaluate - a plain string, a JSON object, or a JSON array. See [State shapes](#state-shapes) below for guidance on which to use. One or more named, typed questions to evaluate against `state`. Each key is your chosen question name; each value is a question object with `type`, `instructions`, and (for `choice`/`score`) `criteria`. See [Noul](/concepts/glide-noul), [Choice](/concepts/glide-choice), and [Score](/concepts/glide-score) for the full per-type request and response shape. Which decision model to use, e.g. `fastino/GLiDE`. Omitting it returns `422 'model' must be provided`. The response echoes it back with the provider prefix stripped (`fastino/GLiDE` → `glide`). ### State shapes `state` is the material every question is evaluated against - think of it as what you'd hand a panel of experts before asking them to make a judgment. | Shape | Useful for | Example | | - | - | - | | String | A single message, article, or passage | `"My card was charged twice."` | | Object | Named fields, related records, or app state | `{"message": "My card was charged twice.", "order_id": "A-104"}` | | Array | A sequence of messages or records | `["Hi", "My order number is A-104.", "My card was charged twice."]` | Use an object when the decision depends on comparing several named parts (a ticket plus the policy it's evaluated against, for example) - it keeps each part labeled and its relationships clear. A plain string is enough when the case is a single self-contained passage. All questions in a request see the same `state` and are evaluated independently against it. ## Confidence Every answer carries a `confidence` value. The answer tells you *what* GLiDE concluded; confidence tells you *whether to act on it* - treat them as two separate axes, not one. | Question type | Formula | Range | | - | - | - | | Noul | `\|2 × noul − 1\|` | `0` (maximum uncertainty, `noul = 0.5`) to `1` (fully certain, `noul = 0` or `1`) | | Choice / Score | `top1 − top2` (probability margin between the best and second-best option or level) | `0` (two options tied) to `1` (one option has \~all the probability mass) | A low-confidence answer isn't wrong - it means the probability mass is spread across two or more outcomes instead of concentrated on one, which is itself useful signal. A common pattern is **confidence-gated routing**: act automatically on high-confidence answers, and route low-confidence ones to a fallback (human review, a broader category, a secondary check): ```python theme={null} answer = response["answers"]["department"] if answer["confidence"] >= 0.6: route_to(answer["choice"]) else: route_to("triage-queue") # ambiguous - let a human or a broader handler decide ``` Tune the threshold on real data for your use case rather than assuming `0.5` is correct - confidence is calibrated per model, not guaranteed to map onto any particular business tolerance for ambiguity. Each primitive page has a worked example and more on using its result: [Noul](/concepts/glide-noul), [Choice](/concepts/glide-choice), [Score](/concepts/glide-score). ## Combining multiple questions Ask multiple questions of different types against the same `state` in a single call. All questions are evaluated together in one round trip. ```bash cURL theme={null} curl -s https://api.fastino.ai/v1/systemone \ -H "X-API-Key: $FASTINO_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "fastino/GLiDE", "state": "Refund request: the receipt is attached, the purchase was 10 days ago, and refunds are allowed within 30 days.", "questions": { "department": { "type": "choice", "instructions": "Which team should handle this request?", "criteria": { "billing": "Payment or charge disputes", "returns": "Refund or return requests", "shipping": "Delivery or shipping issues" } }, "urgency": { "type": "score", "instructions": "How urgent is this request?", "criteria": [ "low urgency, can wait", "medium urgency, handle soon", "high urgency, handle immediately" ] } } }' ``` Response: ```json theme={null} { "model": "glide", "answers": { "department": { "type": "choice", "choice": "returns", "confidence": 0.9992611288391886, "probabilities": { "billing": 0.00031500429476013744, "returns": 0.9995761331339488, "shipping": 0.00010886257129113499 } }, "urgency": { "type": "score", "score": 0, "expected_level": 0.27621539375795195, "confidence": 0.4999999998141525, "probabilities": { "0": 0.7412615353520668, "1": 0.24126153553791435, "2": 0.017476929110018805 }, "legend": { "0": "low urgency, can wait", "1": "medium urgency, handle soon", "2": "high urgency, handle immediately" } } }, "usage": { "input_tokens": 743, "output_tokens": 252 }, "token_usage": 995 } ``` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.