Methodology and sources
methodologyReturn the index methodology: indicators, weights, direction, sources.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
methodologyReturn the index methodology: indicators, weights, direction, sources.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 declare readOnlyHint, idempotentHint, and destructiveHint, establishing a safe read operation. The description adds what the methodology covers (indicators, weights, direction, sources) but no additional behavioral traits such as pagination, formatting, or authorization. This falls short of adding rich context beyond 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?
The description is a single sentence, highly concise, and front-loaded with the action ('Return the index methodology') followed by a compact enumeration of contents. Every word adds value with no redundancy.
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?
For a simple, parameterless tool with an output schema and full annotation coverage, the description is complete. It conveys the essential purpose and scope of the return value, leaving no critical gaps for an agent to understand what to expect.
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 the baseline is 4. The description properly compensates by explaining what the tool returns, which is the sole semantic content needed. No schema parameter descriptions are necessary.
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 uses a specific verb 'Return' and a precise resource 'index methodology', listing the contained elements (indicators, weights, direction, sources). This clearly distinguishes it from sibling tools that return actual data or comparisons.
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 gives no indication of when to use this tool versus alternatives. It doesn't mention any contrasting tools, prerequisites, or explicit usage scenarios. The title partially implies its purpose, but the description could clarify that this is for understanding index construction rather than accessing data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.