get_cracks_indexReturn the full country ranking for the latest published snapshot.
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Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish this as a safe, read-only, idempotent operation. The description adds useful context by specifying that it returns data from the latest published snapshot (not live) and that the ranking is full (implying no pagination). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no wasted words. It is front-loaded with the action and result, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, zero parameters, and presence of an output schema, the description covers the essential aspects. It lacks an explicit mention of the cracks index domain, but the tool name and title provide that context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is complete by default. The description adds no parameter-specific meaning but appropriately clarifies what the parameterless operation returns, which is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the full country ranking from the latest published snapshot. It uses a specific verb ('Return') and resource ('country ranking'), and the scope ('full', 'latest') distinguishes it from sibling tools like indicator_ranking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions or refer to sibling tools, leaving the agent to infer appropriate usage from the name and title alone.
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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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.
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.
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.
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.