declaration_by_agrnThe declaration/activation for an Australian Government Reference Number, merged across sources with the full affected-LGA list.
Requires the "declarations" entitlement on the API key. Accounts without it get a clear error rather than an empty result, so an empty response never means "not entitled".
| Name | Required | Description | Default |
|---|---|---|---|
| agrn | Yes |
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?
The readOnlyHint annotation already establishes safety, and the description adds valuable behavioral context: the required entitlement and the important distinction between an error from lack of entitlement versus an empty result. It also clarifies the data-merging and LGA-list behavior.
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?
Two sentences carry all essential information with no filler. The main purpose is front-loaded, and the auth/error nuance is placed second where it can be absorbed without distracting from the tool's primary function.
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 single-parameter lookup with no output schema, the description adequately covers what the tool returns (declaration/activation merged across sources with full affected-LGA list), who can call it, and how errors behave. Nothing necessary for a correct call is missing.
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?
With 0% schema description coverage, the description compensates by expanding AGRN to 'Australian Government Reference Number' and clarifying it identifies a declaration/activation. It provides the core semantic meaning for the single parameter, though it does not give format or example.
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 identifies the resource as a declaration/activation for an Australian Government Reference Number and distinguishes it by noting the merged-across-sources scope and full affected-LGA list. An explicit verb like 'retrieves' is missing, but the title and phrasing make the read/lookup intent clear.
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 clear context: this is the tool for looking up a single declaration/activation by AGRN with cross-source merging and the full affected-LGA list. It also provides a prerequisite, the 'declarations' entitlement. It does not explicitly describe when to use other sibling tools, but the by-identifier purpose is unambiguous.
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.
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.
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.
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.
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.