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Bigred97

aemo-mcp

latest

Retrieve the most recent interval data for NEM datasets such as dispatch prices or generation mix. Apply optional filters to narrow results by region or fuel type.

Instructions

Return the most recent interval(s) for a NEM dataset.

For 5-min feeds (dispatch_price, dispatch_region, interconnector_flows, generation_scada): returns the most recent 5-minute interval, typically 1-2 minutes after the interval close.

For 30-min feeds (rooftop_pv, predispatch_30min): the most recent half-hour.

For daily feeds (daily_summary): yesterday's data.

Examples: # Current NSW spot price resp = await latest("dispatch_price", filters={"region": "NSW1"})

# Current generation mix in QLD
resp = await latest("generation_scada", filters={"region": "QLD1"})

# Current flow across Heywood
resp = await latest("interconnector_flows", filters={"interconnector": "V-SA"})

Returns: DataResponse with one observation per filtered (dimension, metric) tuple at the most recent interval. stale=True flag indicates the most recent interval is older than 2× the feed cadence (NEMWEB delay).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYesDataset ID like 'dispatch_price'. Use search_datasets() to discover.
filtersNoOptional filter dict. Same shape as get_data — narrow to a region, interconnector, fuel, etc.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYes
dataset_nameYes
queryNo
interval_startNo
interval_endNo
unitNo
recordsNo
csvNo
sourceNoAustralian Energy Market Operator
attributionNoSource: Australian Energy Market Operator (AEMO), NEMWEB. Used under AEMO's Copyright Permissions (general permission for any purpose with accurate attribution). https://aemo.com.au/privacy-and-legal-notices/copyright-permissions
source_urlYes
retrieved_atYes
staleNo
server_versionNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description fully discloses behavior: typical delays after interval close, stale flag logic, and feed-specific cadence. This is comprehensive and additive.

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 well-structured: summary line, detailed breakdown by feed type, examples, and return format. Every sentence serves a purpose without 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?

Given the tool's complexity, the description covers inputs, behavior per feed type, and return details (DataResponse with stale flag). With an output schema present, it is sufficiently complete.

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?

With 100% schema coverage, the description still adds value through usage examples and behavioral context per feed type, surpassing the baseline of 3.

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 states 'Return the most recent interval(s) for a NEM dataset' with clear verb and resource. It provides specific details per feed type and examples, making the purpose unmistakable.

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 description clearly implies when to use (for latest data) and explains cadence per feed type, but does not explicitly contrast with siblings like get_data or search_datasets.

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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