The Cracks Index

Rank areas by one indicator

indicator_ranking

Read-onlyIdempotent

Rank all areas by a single chosen indicator.

Returns every area's value for one indicator, ordered best-first by the
direction-corrected ``normalized_score`` (a higher normalised score
always means fewer cracks on that indicator). The raw value and unit are
included so the figure can be quoted directly.

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

Input Schema

TableJSON Schema

Name	Required	Description	Default
`level`	No	Area level to rank: 'country', 'nuts2' (EU regions) or 'gemeente' (Dutch municipalities). Defaults to 'country'.	country
`limit`	No	Maximum number of areas to return (1-500, default 200).
`indicator_key`	Yes	One of the six Cracks Index indicators: 'problem_debt', 'eviction_rate', 'mh_treatment_gap', 'youth_care_unmet', 'food_insecurity' or 'material_deprivation'. See the 'methodology' tool for definitions.

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 readOnly and idempotent hints, and the description adds valuable context: read-only, area-level aggregates only, no personal data, and the direction-corrected normalized_score meaning. This goes beyond the annotations without contradicting them.

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 four sentences, front-loaded with the primary action, and every sentence adds meaningful detail (score direction, returned values, privacy). No fluff or redundancy.

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?

With full schema coverage, strong annotations, and an output schema present, the description provides sufficient context for the tool's purpose, return behavior, and safety profile. No critical gaps remain.

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?

The input schema already covers 100% of parameters with clear descriptions, so the baseline is 3. The description's mention of normalized_score and raw values relates more to output than to parameter syntax, adding minimal extra parameter-level meaning.

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 opens with a specific verb and resource: 'Rank all areas by a single chosen indicator.' It clearly distinguishes itself from sibling tools by focusing on broad area-level ranking by one indicator, and the following sentences explain the ordering and returned values.

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 scope is clearly stated ('all areas', 'single chosen indicator'), which gives the agent a strong sense of when to use it. However, it does not explicitly name alternatives for scenarios like comparing two specific regions, so it falls short of the top score.

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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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.

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