Normalize Weights

math.normalize_weights

ProductionBounded custom (Class B)Deterministicstrictinstantv1.0.0

No network

Overview

Normalize a bounded vector of decimal weights to an explicit target. Inputs are bounded plain decimals, output order follows input order, and no currency, policy, materiality threshold, market data, or ambient default is inferred.

For Normalize Weights, we publish the exact bounded decimal rule and audit fields so you do not have to trust approximate prompt arithmetic.

Reliability

Normalize Weights is STRICT and stateless: the same bounded input produces the same normalized output. DECIMAL_INVALID means a value is malformed or outside the 100-digit/scale-40 ceilings; fix it before retrying. ITEM_LIMIT_EXCEEDED means an array exceeds 10,000 entries; split it. ZERO_DENOMINATOR means a denominator or weight sum is zero; change it or select the documented zero policy. ROUNDING_INVALID means mode, scale, or quantization is invalid; send a supported mode and scale. ALLOCATION_INVALID means weights, ids, or total violate the published allocation rules; correct the named structure.

Context footprint

For Normalize Weights, one bounded call replaces an error-prone arithmetic prompt and returns normalized decimal strings. A successful call costs 1 execution credit.

When to use it

When a weight vector must be rescaled to a target total, including a default target of 1.

When the weights already sum to the target, or the sum is zero and no rescaling is defined.

Scope

Note

Normalize a bounded vector of decimal weights to an explicit target

Non-goals

Does not infer a rounding, materiality, currency, or business policy
Does not fetch market data or invoke another public skill
Does not accept unbounded arrays or binary floating-point semantics

Properties

IdempotentRetry safeStreaming supportedFile input supportedRequires external service

Capabilities

data-transformationmath

Cost & billing

Flat rate per invocation

MetercallsBillable onsuccessCost per call1 credit

File handling

Accepts file_refProduces file_refMax input64 KB

How we handle your data

Sensitive input, safe output

What this means

This skill may receive sensitive content, but it does not target sensitive data and returns only a structured non-sensitive result.

Squillify guarantees

Runs inside Squillify
This skill runs inside Squillify.
Payloads are not sent to an external service by this skill.
Squillify does not permanently store submitted payloads.
Telemetry records metadata only, not submitted content.
Submitted payloads are not used for training.
Submitted payloads are not reviewed by humans.
This skill does not target sensitive data.
The response does not contain submitted content.

Your responsibility

Squillify does not determine whether submitted content is sensitive. Your application is responsible for deciding what data it is allowed to submit. Your application is responsible for securing the response.

Read the Microskill Data Handling Policy

Input schema

Field	Type	Required	Description
weights	array	Yes	Required 1 to 10,000 plain-decimal weights whose sum is not zero; negative values are accepted.
target	string	No	Optional plain-decimal target total; omitted means 1.

Output schema

Field	Type	Required	Description
normalizedWeights	array	Yes	Array of 1 to 10,000 normalized decimal string items in input order.
originalTotal	string	Yes	Exact sum of the supplied weights.
target	string	Yes	Resolved target, including the default 1.
residual	string	Yes	target minus normalized sum; normally 0.

API contract

POST /v1/execute

curl

curl -sS -X POST "$BASE/v1/execute" -H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' -d '{"skillKey":"math.normalize_weights","input":{"weights":["2","3"]}}'

Integrations

TypeScript SDK

import { Squillify } from "@squillify/sdk";

const sq = new Squillify({ apiKey: process.env.SQUILLIFY_API_KEY });

const { output } = await sq.execute("math.normalize_weights", {"weights":["2","3"]});

Errors

Code	HTTP	Retryable	Description
VALIDATION_ERROR	400	No	The request payload failed schema validation.
UNAUTHORIZED	401	No	Missing or invalid API key.
SKILL_NOT_ACCESSIBLE	403	No	The API key is not granted access to this skill.
SKILL_NOT_AVAILABLE_FOR_PLAN	403	No	This skill is not included in your current plan.
PLAN_ELIGIBILITY_UNAVAILABLE	503	Yes	Plan eligibility could not be decided. Retry after backoff.
SKILL_NOT_FOUND	404	No	The requested skill or version does not exist.
TENANT_RATE_LIMITED	429	Yes	Request rate limit exceeded. Retry after backoff.
QUOTA_EXCEEDED	429	Yes	Plan quota exhausted. Retryable once the quota period resets.
EXECUTION_TIMEOUT	504	Yes	Execution exceeded the allowed time budget.
DECIMAL_INVALID	400	No	The request payload failed this skill's input validation.
ITEM_LIMIT_EXCEEDED	429	No	A size, quota, rate, or time limit was exceeded.
ZERO_DENOMINATOR	400	No	The request payload failed this skill's input validation.
ROUNDING_INVALID	400	No	The request payload failed this skill's input validation.
ALLOCATION_INVALID	400	No	The request payload failed this skill's input validation.

Other limits

Limit	Value
Recommended inline bytes	32 KiB

Limitations

Does not infer a rounding, materiality, currency, or business policy
Does not fetch market data or invoke another public skill
Does not accept unbounded arrays or binary floating-point semantics
When the weights already sum to the target, or the sum is zero and no rescaling is defined.
Do not use for approximate floating-point analytics or unbounded datasets

How to call

POST /v1/execute (requires authentication)

Request bodyjson

{
  "skillKey": "math.normalize_weights",
  "input": {
    "weights": [
      "2",
      "3"
    ]
  }
}

Examples

Normalize 2:3 to one

Inputjson

{
  "weights": [
    "2",
    "3"
  ]
}

Expected outputjson

{
  "normalizedWeights": [
    "0.4",
    "0.6"
  ],
  "residual": "0",
  "target": "1",
  "originalTotal": "5"
}

Normalize signed weights to one hundred