Burs-IA Utils

Histograma

stats-histogram

Read-onlyIdempotent

Agrupa números en intervalos de igual ancho y devuelve conteos. Cuándo: un resultado numérico tiene que ser exacto o reproducible y no estimado. No para: calcular percentiles (stats-percentile). 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: Buckets numbers into equal-width bins (count or explicit edges), returning bin ranges and counts; the last bin includes its upper edge. When: a numeric result has to be exact or reproducible instead of estimated. Not for: computing one or more percentiles (stats-percentile). 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
`max`	No	Upper bound (default data max) (number; optional).
`min`	No	Lower bound (default data min) (number; optional).
`bins`	No	Number of bins (integer; optional; default 10; min 1; max 1000).
`values`	Yes	Numbers (array of number; required; at least 1 items).

Output Schema

Name	Required	Description	Default
`bins`	No
`outside`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 2, 2026
- addedInput schema / properties / values / examples
```
Added value: +[
+  [
+    1,
+    2,
+    2,
+    3,
+    9,
+    10
+  ]
+]
```
First observedNov 1, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description still adds material context the annotations cannot express: no network, no stored state, determinism guarantees, and concrete operational limits (64 KB JSON input, 1 s per call, 1 MB result). No contradiction with the annotation profile.

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

Conciseness3/5

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

Each individual sentence (when, not-for, side effects, determinism, limits) earns its place and the critical scoping leads. However, the entire block is duplicated verbatim in Spanish and English, roughly doubling length without adding information for a single reader.

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

Completeness4/5

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 need no explanation, and side effects, determinism, limits, and the sibling routing are all covered for this small 4-parameter tool. The only incompleteness is the unsupported "explicit edges" capability claim, which the schema does not back.

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 documents min/max/bins/values fully, so the baseline is 3. The description adds the genuinely useful statement that the last bin is closed on its upper edge, but it also advertises "count or explicit edges" when the schema exposes no edges parameter — a claim that cannot be satisfied and may mislead.

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?

"Buckets numbers into equal-width bins ... returning bin ranges and counts" names a specific verb, the resource, and the exact output shape, and adds the non-obvious boundary rule (last bin includes its upper edge). It also explicitly separates itself from stats-percentile, so an agent can distinguish it from the ~15 other stats-* siblings without opening a 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?

Provides an explicit "When:" (result must be exact/reproducible rather than estimated) and an explicit "Not for:" naming the alternative tool (stats-percentile). This is the full when/when-not/alternative triad, leaving nothing 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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