The Cracks Index

Where an area sits statistically

area_statistics

Read-onlyIdempotent

Return where one area sits statistically within its own level.

Places an area against its peer group (all areas at the same level in
the latest snapshot): its percentile, the distance from its composite
score to the level median, best and worst, and the handful of areas
nearest to it by score. Useful for answering "is this area typical, or
an outlier?".

Read-only, area-level aggregates only, no personal data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`area`	Yes	An ISO-3166 alpha-3 country code (e.g. 'NLD') or an area code of an EU NUTS-2 region or Dutch municipality (e.g. 'NL32', 'GM0363'). Case-insensitive.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds meaningful transparency by stating 'Read-only, area-level aggregates only, no personal data', which conveys privacy and aggregation characteristics beyond the schema. It also clarifies the data scope (latest snapshot, peer group). This exceeds baseline expectations without contradicting annotations.

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

Conciseness5/5

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

The description is three sentences: the first immediately states the main purpose, the second lists the concrete outputs, and the third adds the use case. Every sentence earns its place with no repetition or filler. It is efficiently front-loaded with the key verb and resource.

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?

Despite having one parameter and rich annotations, the description covers the essential context: the tool computes statistical placement, lists outputs, and clarifies its read-only, aggregate-only nature. With an output schema present, the return value details are handled elsewhere. The description is sufficient for an agent to select and invoke the tool correctly without ambiguity.

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%, so the parameter 'area' is fully documented in the input schema. The description does not add additional parameter-level semantics—it only references 'its own level' which is consistent with the schema's mention of country codes, NUTS-2 regions, and municipalities. Since the schema carries the parameter detail, the description adds no extra value beyond the baseline.

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?

The description clearly states the tool's function: 'Return where one area sits statistically within its own level.' It specifies the exact outputs (percentile, distance to median, best/worst, nearest areas), making it distinct from siblings like indicator_ranking or region_detail. The verb is specific ('Return') and the resource is precise (statistical placement within its peer group).

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?

The description provides a clear use case: 'Useful for answering "is this area typical, or an outlier?"'. This gives context for when to use the tool. It does not explicitly name alternative tools or exclusion criteria, but the stated purpose separates it from comparison or ranking tools. No explicit when-not-to-use is mentioned, so it falls short of a 5.

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

All The Cracks Index tools Inspect

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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct query: rankings, country details, region details, comparisons, trends, correlations, methodology, and improvement guidance. Despite minor overlaps (e.g., country_fix and improvement_guidance), descriptions clearly differentiate them, so an agent can reliably select the correct tool.

Naming Consistency3/5

Tool names mix patterns: some start with verbs (compare_countries, get_cracks_index), others with nouns (area_statistics, country_detail, methodology). While readable and clear, the lack of a consistent verb_noun or noun_verb paradigm reduces predictability for an agent.

Tool Count5/5

With 13 tools covering the full spectrum of index queries—rankings, details, comparisons, trends, correlations, methodology, and improvement guidance—the count is well-scoped for the domain. No tool feels superfluous, and the set is neither too sparse nor too bloated.

Completeness5/5

The tool surface provides complete CRUD-like coverage for the Cracks Index: full ranking, per-area detail and breakdown, comparisons, trends, top movers, indicator correlations, ranking by indicator, methodology, and improvement guidance. No obvious gaps exist for common agent workflows.

Resources

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