Burs-IA Utils

Describir estructura JSON

json-describe

Read-onlyIdempotent

Resume la estructura de un JSON: profundidad, conteos por tipo, tamaño y rutas distintas. Cuándo: hay que transformar, comparar o revisar con exactitud datos estructurados (JSON, CSV, YAML, XML, arreglos). No para: convertir documentos de ejemplo (json-schema-from-samples). 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: Summarizes a JSON value: nesting depth, counts of each type, number of keys, serialized size, and the set of distinct paths (arrays collapsed to []). When: structured data (JSON, CSV, YAML, XML, arrays) has to be transformed, compared or checked exactly. Not for: turning sample documents (json-schema-from-samples). 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).
`max_paths`	No	Max paths to list (integer; optional; default 200; min 0; max 5000).

Output Schema

Name	Required	Description	Default
`bytes`	No
`depth`	No
`paths`	No
`counts`	No
`distinct_paths`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 2, 2026

addedInput schema / properties / value / examples

Added value: +[
+  {
+    "a": [
+      1,
+      2
+    ],
+    "b": {
+      "c": null
+    }
+  }
+]

First observedNov 1, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so restating 'no side effects, read-only, no network, no state' earns little credit. The description does add genuinely new behavioral facts not in structured data: hard limits of 64 KB input, 1 s per call, and 1 MB result, plus the determinism guarantee.

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?

Front-loaded with the purpose, then clearly labeled sections (When / Not for / Side effects / Deterministic / Limits) that are easy to scan. The only waste is that the entire content is duplicated verbatim in Spanish and English, roughly doubling length without adding information.

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?

For a two-parameter read-only tool with an output schema and full annotation coverage, this is complete: what it computes, when to reach for it, what to use instead, safety profile, determinism, and the operational limits an agent needs to avoid oversized inputs or truncated results.

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?

Schema description coverage is 100% and both parameters (value, max_paths with default 200, range 0-5000) are already documented in the schema, so the baseline of 3 applies. The description adds interpretive detail about output paths (arrays collapsed to []) but says nothing extra about max_paths or the accepted input shapes beyond 'JSON value'.

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 plus the exact outputs produced: nesting depth, counts per type, key count, serialized size, and distinct paths with arrays collapsed to []. That level of detail makes it instantly distinguishable from json-flatten-paths, json-extract or stats-describe, and it explicitly names the sibling it is not (json-schema-from-samples).

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

Usage Guidelines4/5

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

Provides an explicit 'When' (structured data has to be transformed, compared or checked exactly) and an explicit 'Not for' naming json-schema-from-samples, which is a real exclusion. The 'when' is broad enough that it could also match several array-*/json-* siblings, but the one named alternative plus the concrete output list keeps usage reasonably well-scoped.

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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