Data source attributions
get_attributionRead-only
Returns attribution information for all data sources, including licence details. Required for CC BY compliance.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
DataQuoll
by io.dataquoll
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers the safety profile. The description adds meaningful behavioral context by stating that it returns attribution information for all data sources and includes licence details, which goes beyond the bare annotation.
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 a single sentence with a clear subject, action, and scope, followed by a purposeful compliance note. Every word earns its place; there is 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?
For a zero-parameter, read-only metadata tool, the description fully equips an agent to select and invoke it. It explains what data is returned, highlights the licence detail, and states the compliance purpose. No output schema is needed for this level of simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and 100% schema coverage vacuously, so the baseline of 4 applies. There are no parameter semantics to document, and the description appropriately focuses on the output instead.
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 uses a specific verb ('Returns') and names the exact resource ('attribution information for all data sources'), including licence details. This clearly distinguishes it from the sibling tools, which all concern domain-specific declarations, incidents, or gauges.
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 phrase 'Required for CC BY compliance' gives a clear context for when this tool should be used. There are no overlapping sibling tools offering similar attribution data, so explicit exclusion guidance is less necessary, though the description does not spell out when not to use it.
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
A3.9/5.0
Disambiguation4/5
Most tools target a distinct resource and action, and the descriptions are detailed enough to separate declaration lookups, hazard history, incidents, events, and gauges. A couple of pairs could still be confused at first glance, such as declarations_by_point vs hazard_history_by_point or list_events vs list_incidents, but the descriptions resolve the boundaries.
Naming Consistency4/5
The naming largely follows a clear get_/list_ convention for single resources versus collections, with lookup-style names like declarations_by_point and declarations_by_postcode. Minor deviations such as incident_snapshot, nearby_incidents, and the singular declaration_by_agrn prevent a perfect score.
Tool Count4/5
19 tools is on the heavier side, but the count is justified by the broad domain covering current incidents, historical incidents, clustered events, declarations, river gauges, hazard history, schema discovery, attribution, and feed health. Each tool appears to earn its place, though the set is larger than the ideal 3-15 range for a tightly scoped server.
Completeness5/5
The surface is remarkably complete for a read-only emergency/disaster data API: current and historical incidents, event clustering, incident snapshots, nearby queries, declaration lookups by multiple keys, gauge readings and summaries, hazard history, schema enums, attribution, and source feed status are all covered. There are no obvious dead ends or missing core operations for the stated domain.