Burs-IA Utils

Inferir JSON Schema de ejemplos

json-schema-from-samples

Read-onlyIdempotent

Convierte documentos de ejemplo (p. ej. respuestas de una API) en un JSON Schema inicial: une los tipos vistos en cada ruta, marca como requeridas las claves presentes en todos y describe los ítems. Cuándo: hay que transformar, comparar o revisar con exactitud datos estructurados (JSON, CSV, YAML, XML, arreglos). No para: validar un JSON contra un JSON Schema (json-schema-validate). Efectos secundarios: ninguno (solo lectura, sin red, sin estado guardado). Determinista: la misma entrada da la misma salida. Límites: entrada JSON de hasta 64 KB, 1 s por llamada, resultado de hasta 1 MB.

EN: Turns sample documents (for example API replies) into a starter JSON Schema: merges the types seen at each path, marks keys present in every sample as required and describes array items. When: structured data (JSON, CSV, YAML, XML, arrays) has to be transformed, compared or checked exactly. [EN completo / full EN: inputSchema.description]

Input Schema

Name	Required	Description	Default
`samples`	Yes	Sample values (same shape expected) (array; required; at least 1 items; up to 1000 items).

Output Schema

Name	Required	Description	Default
`schema`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 2, 2026

addedInput schema / properties / samples / examples

Added value: +[
+  [
+    {
+      "id": 1,
+      "name": "a",
+      "tags": [
+        "x"
+      ]
+    },
+    {
+      "id": 2.5,
+      "tags": []
+    }
+  ]
+]

Changed1 schema field changedNov 1, 2026

addedInput schema / description

Added value: +"EN: Turns sample documents (for example API replies) into a starter JSON Schema: merges the types seen at each path, marks keys present in every sample as required and describes array items. When: structured data (JSON, CSV, YAML, XML, arrays) has to be transformed, compared or checked exactly. Not for: validating a JSON value against a JSON Schema using a built-in subset (json-schema-validate). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. Limits: JSON input up to 64 KB, 1 s per call, result up to 1 MB."

First observedNov 1, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful context beyond annotations: no network access, no stored state, deterministic output, and concrete limits (64 KB input, 1 s per call, 1 MB result).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The content is front-loaded and organized into purpose, when, not-for, side effects, determinism, and limits. However, the bilingual duplication and the truncated English line ('EN completo / full EN: inputSchema.description') add avoidable length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given one parameter, full schema coverage, rich annotations, and an output schema, the description is complete enough: it covers purpose, alternatives, side effects, determinism, and operational limits. No critical invocation detail is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single 'samples' parameter is documented with examples, so the baseline is 3. The description adds meaning by clarifying that samples are example documents such as API replies and by stating the 64 KB input limit, which is not in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: converts sample documents into a starter JSON Schema, and explains the merge/required/array-item behavior. It also explicitly distinguishes itself from json-schema-validate, so an agent can select it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit 'Cuándo' condition for structured data transformation/comparison/checking and an explicit 'No para' exclusion naming json-schema-validate as the alternative. This is clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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