Burs-IA Utils

JSON a YAML

yaml-build

Read-onlyIdempotent

Serializa un valor JSON como YAML en bloque, con comillas cuando hace falta. Cuándo: hay que transformar, comparar o revisar con exactitud datos estructurados (JSON, CSV, YAML, XML, arreglos). No para: convertir un subconjunto seguro de YAML a JSON (yaml-parse). 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: Serializes a JSON value as block-style YAML, quoting strings that would otherwise be read as numbers, booleans, null or YAML syntax. When: structured data (JSON, CSV, YAML, XML, arrays) has to be transformed, compared or checked exactly. Not for: parsing a safe YAML subset (yaml-parse). 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.

Input Schema

Name	Required	Description	Default
`value`	Yes	Any JSON value (any JSON value; required).

Output Schema

Name	Required	Description	Default
`yaml`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 2, 2026

addedInput schema / properties / value / examples

Added value: +[
+  {
+    "name": "Burs-IA",
+    "nested": {
+      "x": null
+    },
+    "port": 8080,
+    "tags": [
+      "a",
+      "true"
+    ]
+  }
+]

First observedNov 1, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, and the description partly restates these. It does add value beyond them: the quote-when-ambiguous rule, determinism, and concrete operational limits (64 KB input, 1 s per call, 1 MB output) that the annotations cannot express.

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?

Each language block is tight, front-loads the verb and uses labeled clauses (When / Not for / Side effects / Limits) that scan well. The full Spanish+English duplication doubles length, though that appears to be a deliberate localization convention rather than padding.

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?

An output schema exists so return values needn't be explained; within that, the description covers input type, transformation semantics, determinism, side effects, limits and sibling routing. Nothing needed to call it correctly is missing.

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

Parameters3/5

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

Only one parameter with 100% schema description coverage and an inline example, so the schema carries parameter meaning. The description adds nothing about the 'value' parameter specifically (e.g., no note on how nested arrays/objects are rendered), which is the expected baseline for fully-covered schemas.

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?

Names a specific verb+resource: serialize a JSON value as block-style YAML, and even specifies block style and the quoting rule. It explicitly distinguishes itself from yaml-parse, so an agent can route between them without opening either 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?

Has explicit 'When' (transform/compare/check exact structured data) and 'Not for' (parsing a safe YAML subset → yaml-parse) clauses, naming the alternative tool directly. Nothing is left to inference.

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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