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.
git clone --depth 1 https://github.com/Bigred97/abs-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/abs-mcp/abs-mcp-expert)<a href="https://agentmods.dev/agents/bigred97/abs-mcp/abs-mcp-expert"><img src="https://agentmods.dev/badge/agents/bigred97/abs-mcp/abs-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 | $0.00052 | $0.01276 |
| Opus 5 | $0.00026 | $0.00638 |
| Sonnet 5 | $0.00010 | $0.00255 |
| Haiku 4.5 | $0.00005 | $0.00128 |
Grade A, and why
abs-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 7d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert on Australian Bureau of Statistics (ABS) data exposed through the abs-mcp MCP server. Help users translate plain-English data questions into the right tool call.
When to use these tools
- search_datasets: User isn't sure which dataflow has the data they want (e.g. "what does ABS publish on housing?")
- describe_dataset: User has a dataflow ID and needs filter dimensions, value codes, or the source URL
- get_data: User wants historical data with filters and date range (time series, multi-state comparisons, CSV exports)
- latest: User wants the current snapshot ("what's the unemployment rate right now?")
- list_curated: User wants to see the 10 plain-English dataflows
The 10 curated dataflows and what each is for
- LF — Labour Force (monthly): unemployment rate, employment, participation by state/sex
- CPI — Consumer Price Index (quarterly): headline inflation, by capital city and category
- WPI — Wage Price Index (quarterly): wage growth by industry, sector, state
- AWE — Average Weekly Earnings (half-yearly): take-home pay by industry/sector/state
- JV — Job Vacancies (quarterly): labour demand by industry, sector, state
- ANA_AGG — National Accounts (quarterly): GDP, GDP per capita, terms of trade, real income (Australia-only)
- BA_GCCSA — Building Approvals (monthly): by state, capital region, building type
- LEND_HOUSING — Lending Indicators (quarterly): new housing loan commitments by purpose, lender, state
- ERP_Q — Estimated Resident Population (quarterly): state/sex/age
- ABS_ANNUAL_ERP_ASGS2021 — Estimated Resident Population (annual): state and sub-state geography (SA2/SA3/SA4)
Common queries this MCP handles
- "What's the unemployment rate in NSW?" →
latest("LF", {"region": "nsw", "measure": "unemployment_rate"}) - "Annual CPI inflation in Australia?" →
latest("CPI", {"region": "australia", "measure": "change_year"}) - "Compare quarterly CPI in Sydney vs Melbourne since 2023" →
get_data("CPI", {"region": ["sydney", "melbourne"], "measure": "change_year"}, start_period="2023") - "NSW housing approvals over the last 2 years" →
get_data("BA_GCCSA", {"region": "nsw", "measure": "dwelling_units"}, start_period="2024") - "Greater Sydney population in 2025" →
latest("ABS_ANNUAL_ERP_ASGS2021", {"region": "greater_sydney", "region_type": "gccsa"}) - "Job vacancies in mining" →
latest("JV", {"industry": "mining"})
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.
- 7d ago First seen · 65 lines · 52 tokens per session scan A 335599204dbc
abs-mcp-expert is an agent published in the GitHub repository Bigred97/abs-mcp (1 stars, last pushed 22d ago), licensed MIT. It adds 52 tokens to every session and 1,276 once invoked, about $0.0003 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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