Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brensch/scadaminer-ai-toolkit --skill nem-market-analysisgit clone --depth 1 https://github.com/brensch/scadaminer-ai-toolkitWrote 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/skills/brensch/scadaminer-ai-toolkit/nem-market-analysis)<a href="https://agentmods.dev/skills/brensch/scadaminer-ai-toolkit/nem-market-analysis"><img src="https://agentmods.dev/badge/skills/brensch/scadaminer-ai-toolkit/nem-market-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brensch/scadaminer-ai-toolkit/nem-market-analysis"><img src="https://agentmods.dev/badge/skills/brensch/scadaminer-ai-toolkit/nem-market-analysis.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00103 | $0.00870 |
| Opus 5 | $0.00051 | $0.00435 |
| Sonnet 5 | $0.00021 | $0.00174 |
| Haiku 4.5 | $0.00010 | $0.00087 |
Grade A, and why
nem-market-analysis 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 11d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NEM Market Analysis (SCADA Miner)
This skill helps you answer Australian National Electricity Market (NEM) questions accurately using the SCADA Miner MCP server, which exposes a ClickHouse warehouse of AEMO market data. Apply it whenever the user asks about NEM/AEMO topics (prices, generation, FCAS, interconnectors, constraints, demand, bids, revenue) and the SCADA Miner tools are connected.
Key facts
- NEM time is Australia/Brisbane (UTC+10, no daylight saving). Do date arithmetic in that zone.
- Regions are
NSW1,QLD1,SA1,TAS1,VIC1. - All warehouse access is read-only.
Workflow
- Open a trace. Call
start_questionwith the user's question and pass the returnedquestion_idon every subsequent tool call in the same answer turn. - Resolve entities. For each station / DUID / region / interconnector / fuel
term, call
search_entitiesand pick the candidate that fits the question's context. Ignore weak matches for generic English words (e.g. "demand", "power"). - Anchor time. If the question is time-bounded, call
get_data_freshnessto clamp the range to available data. Resolve undated phrases (e.g. "March 3", "last week") to the most recent past occurrence and always restate the inferred year in your answer. Ask the user if a date is genuinely ambiguous. - Prefer a capability. Call
list_capabilities; when one matches, userun_capability(withexecute: true) — it returns pre-validated SQL, a chart, and often a deterministic answer. Always prefer this over hand-written SQL. - Fall back carefully. If no capability fits, locate the table with
list_tables(bydomain/keywords) orsearch_columns(by measure), then callget_table_schemaand read itscaveats(sign conventions, double-counting, partial coverage) before composing SQL. Execute withexecute_sql. Add a time-columnWHEREfilter so ClickHouse can prune. - Chart when it helps. Use
build_chartfor trends, rankings, breakdowns, and comparisons. For multi-series data setcolorto the category instead of drawing one line through repeated timestamps. Use one chart per period for period-over-period comparisons, each titled with its period. - Answer. Concise, analyst style: cite exact numbers with units, state the resolved date range, and note caveats. Keep it brief unless detail is asked for.
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.
- 11d ago First seen · 66 lines · 103 tokens per session scan A 13b2ae51a7f6
nem-market-analysis is a skill published in the GitHub repository brensch/scadaminer-ai-toolkit (0 stars, last pushed 1mo ago), licensed MIT. It adds 103 tokens to every session and 870 once invoked, about $0.0005 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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