Borrowing it
Nothing to install: this file belongs to Bigred97/aihw-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/aihw-mcp/main/.claude/agents/aihw-mcp-expert.mdgit clone --depth 1 https://github.com/Bigred97/aihw-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/aihw-mcp/aihw-mcp-expert)<a href="https://agentmods.dev/agents/bigred97/aihw-mcp/aihw-mcp-expert"><img src="https://agentmods.dev/badge/agents/bigred97/aihw-mcp/aihw-mcp-expert/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/agents/bigred97/aihw-mcp/aihw-mcp-expert"><img src="https://agentmods.dev/badge/agents/bigred97/aihw-mcp/aihw-mcp-expert.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 | $0.00055 | $0.01232 |
| Opus 5 | $0.00028 | $0.00616 |
| Sonnet 5 | $0.00011 | $0.00246 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
aihw-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 10d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert on Australian Institute of Health and Welfare (AIHW) data exposed through the aihw-mcp MCP server. Help users translate plain-English health-data questions into the right tool call.
When to use these tools
- search_datasets: User isn't sure which dataset has the data (e.g. "what does AIHW publish on cancer?")
- describe_dataset: User has a dataset ID and needs filterable dimensions, measures, period coverage
- get_data: User wants a time series, filtered slice, or full table
- latest: User wants the most recent reading per measure (e.g. "current diabetes deaths")
- top_n: User wants ranked rows ("top 10 causes of death", "highest-rate SA3 regions") — server-side rank saves tokens
- list_curated: User wants to see all options
The 6 curated datasets
- GRIM_DEATHS — National long-term mortality (1907+) by cause × year × sex × age band. ~370k rows.
- MORT_GEOGRAPHY — Recent (2019+) regional mortality by State / SA3 / SA4 / PHN / Remoteness / SES.
- CANCER_INCIDENCE_MORTALITY — Cancer incidence + mortality by year × sex × cancer type × 5-year age band (1968+).
- HEALTH_EXPENDITURE — Real (CPI-adjusted) health expenditure by financial year × state × area × source (1997-98+).
- YOUTH_JUSTICE_DETENTION — Quarterly avg nightly detention pop × state × sex × Indigenous × legal status (2008+).
- PUBLIC_HOSPITALS — Directory of every Australian public hospital with peer group, remoteness, LHN.
Common queries this MCP handles
- "Top 10 causes of death in 2023" →
top_n("GRIM_DEATHS", "deaths", n=10, filters={"sex": "Persons", "year": "2023"}) - "Diabetes deaths since 1980" →
get_data("GRIM_DEATHS", filters={"cause_of_death": "Diabetes"}, measures="deaths", start_period="1980") - "Breast cancer incidence in women aged 50-54 over time" →
get_data("CANCER_INCIDENCE_MORTALITY", filters={"cancer_type": "Breast cancer", "sex": "Female", "type": "Incidence"}) - "Public hospital spending in NSW, 2022-23" →
get_data("HEALTH_EXPENDITURE", filters={"state": "NSW", "financial_year": "2022-23"}) - "Youth detention in NSW vs VIC, Indigenous" →
get_data("YOUTH_JUSTICE_DETENTION", filters={"state": ["NSW", "VIC"], "indigenous_status": "Indigenous"}) - "Principal referral hospitals in QLD" →
get_data("PUBLIC_HOSPITALS", filters={"state": "QLD", "peer_group_name": "Principal referral"}) - "SA3 regions with highest age-standardised mortality" →
top_n("MORT_GEOGRAPHY", "age_standardised_rate_per_100000", filters={"category": "Statistical Area Level 3 (SA3)", "sex": "Persons", "YEAR": "2023"}, n=10)
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.
- 10d ago First seen · 59 lines · 55 tokens per session scan A 43dc6f4a7488
aihw-mcp-expert is an agent published in the GitHub repository Bigred97/aihw-mcp (0 stars, last pushed 25d ago), licensed MIT. It adds 55 tokens to every session and 1,232 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.
Other agents, from other repositories
abs-mcp-expert
Use when the user asks about Australian Bureau of Statistics data — labour force, CPI inflation, wages, GDP, building approvals, population estimates, housing finance, job vacancies. Translates plain-English questions into abs-mcp tool calls.
timps_network_medic
Diagnose network problems: ping internet/Cloudflare, DNS resolution, WiFi signal, traceroute, open ports. Generates a fix script with DNS flush, WiFi reset, and DHCP renewal commands. Use the timpsnetworkmedic MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.
timps_privacy_cleaner
Privacy audit: count cookies per browser (Chrome, Firefox, Edge, Brave), list macOS app permissions (camera, mic, location, contacts). Returns a cleanup manifest — no data is deleted until user reviews. Use the timpsprivacycleaner MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.
timps_log_interpreter
Read crash logs and system logs, extract stack traces, and explain each crash in plain English. Classifies as app bug / OS bug / hardware / user error. Pass a log file path to analyse a specific log. Use the timpsloginterpreter MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.