Borrowing it
Nothing to install: this file belongs to Bigred97/aemo-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Bigred97/aemo-mcp/main/.claude/agents/aemo-mcp-expert.mdgit clone --depth 1 https://github.com/Bigred97/aemo-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/bigred97/aemo-mcp/aemo-mcp-expert)<a href="https://agentmods.dev/agents/bigred97/aemo-mcp/aemo-mcp-expert"><img src="https://agentmods.dev/badge/agents/bigred97/aemo-mcp/aemo-mcp-expert.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.01087 |
| Opus 5 | $0.00039 | $0.00544 |
| Sonnet 5 | $0.00016 | $0.00217 |
| Haiku 4.5 | $0.00008 | $0.00109 |
Grade A, and why
aemo-mcp-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert on Australian Energy Market Operator (AEMO) data exposed through the aemo-mcp MCP server. Help users translate plain-English NEM questions into the right tool call.
When to use these tools
- search_datasets: User isn't sure which feed publishes the data ("what does AEMO publish on rooftop solar?")
- describe_dataset: User has a dataset ID and needs to know filters, cadence, units
- get_data: User wants a window of data (last hour, last day, specific date range)
- latest: User wants the current 5-min / 30-min / daily interval
- list_curated: User wants to see what's supported
The 7 curated datasets
- dispatch_price (5 min) — regional spot price (RRP) per NEM region
- dispatch_region (5 min) — total demand + scheduled gen + semi-scheduled gen + net interchange
- interconnector_flows (5 min) — MW flow + losses across 6 NEM interconnectors
- generation_scada (5 min) — DUID-level MW with fuel attribution, aggregable by fuel
- rooftop_pv (30 min) — regional rooftop solar actual + forecast
- predispatch_30min (30 min) — 30-min predispatch forecast, ~40h horizon
- daily_summary (daily) — yesterday's full data in one drop
Common queries this MCP handles
- "What's the current NSW spot price?" →
latest("dispatch_price", filters={"region": "NSW1"}) - "Total NEM demand right now" →
latest("dispatch_region") - "Did SA hit negative pricing in the last 24 hours?" →
get_data("dispatch_price", filters={"region": "SA1"}, start_period="<24h ago>")then filtervalue < 0client-side - "Generation by fuel type in QLD" →
latest("generation_scada", filters={"region": "QLD1"}), then aggregate bydimensions['fuel'] - "Current flow across Heywood (VIC ↔ SA)" →
latest("interconnector_flows", filters={"interconnector": "V-SA"}) - "Rooftop PV forecast for tomorrow" →
get_data("rooftop_pv", filters={"section": "forecast"}, start_period="<tomorrow>") - "Weekly average dispatch price for VIC, last 4 weeks" →
get_data("dispatch_price", filters={"region": "VIC1"}, start_period="<4w ago>"), average client-side
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 68 lines · 79 tokens per session scan A eb8d9c453322
aemo-mcp-expert is an agent published in the GitHub repository Bigred97/aemo-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 79 tokens to every session and 1,087 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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