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 wardawgmalvicious/agent-config --skill fabric-warehouse-monitoringgit clone --depth 1 https://github.com/wardawgmalvicious/agent-configWrote 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/wardawgmalvicious/agent-config/fabric-warehouse-monitoring)<a href="https://agentmods.dev/skills/wardawgmalvicious/agent-config/fabric-warehouse-monitoring"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/fabric-warehouse-monitoring/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/wardawgmalvicious/agent-config/fabric-warehouse-monitoring"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/fabric-warehouse-monitoring.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 | $0.00102 | $0.01393 |
| Opus 5 | $0.00051 | $0.00696 |
| Sonnet 5 | $0.00020 | $0.00279 |
| Haiku 4.5 | $0.00010 | $0.00139 |
Grade A, and why
fabric-warehouse-monitoring 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 today.
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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring & diagnostics
Query Labels
SELECT ... FROM ...
OPTION (LABEL = 'PROJECT_Module_Description');
Labels appear in queryinsights.exec_requests_history.label. Use for tracking, filtering, and performance analysis.
Query Insights (30-day retention)
| View | Purpose |
|---|---|
queryinsights.exec_requests_history |
Every completed query: status, duration, CPU, data scanned |
queryinsights.exec_sessions_history |
Session history: login info, times |
queryinsights.long_running_queries |
Aggregated: median vs last-run time |
queryinsights.frequently_run_queries |
Run counts, execution times for recurring patterns |
Gotcha: Data appears with up to 15 minutes delay. After creating a new warehouse, views may return "Invalid object name" — wait ~2 minutes.
Top Expensive Queries
SELECT TOP 10
distributed_statement_id, query_hash, label,
total_elapsed_time_ms, allocated_cpu_time_ms,
data_scanned_remote_storage_mb, result_cache_hit
FROM queryinsights.exec_requests_history
ORDER BY allocated_cpu_time_ms DESC;
Aggregate by query_hash over the last 7 days to find recurring expensive patterns.
To find the queries behind a Capacity Metrics billing interval, correlate by time, not by ID: the Metrics app's Operation Id no longer maps to distributed_statement_id (Learn, confirmed 2026-09-11). Take the interval's Start and End from the app's Background operations table, then select the requests that overlapped it:
DECLARE @Start_Time DATETIME2(0) = '2026-08-04 8:00:00'
,@End_Time DATETIME2(0) = '2026-08-04 9:00:00'
SELECT [database_name],
sql_pool_name,
distributed_statement_id,
login_name,
allocated_cpu_time_ms / 1000.0 AS vcore_seconds
FROM queryinsights.exec_requests_history
WHERE start_time < @End_Time
AND end_time > @Start_Time;
DMVs (Live State)
| DMV | Shows | Min Role |
|---|---|---|
sys.dm_exec_connections |
Active connections (session_id, client_address) | Admin only |
sys.dm_exec_sessions |
Authenticated sessions (login_name, login_time, status) | All roles (own sessions) |
sys.dm_exec_requests |
Active requests (command, start_time, total_elapsed_time) | All roles (own requests) |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today Changed · +18 lines e7f571735d7b
- 2d ago Changed ac9dd9df95d7
- 8d ago Changed · +5 lines 83b3fb84f71a
- 12d ago First seen · 99 lines · 102 tokens per session scan A d3d9db5acf1e
fabric-warehouse-monitoring is a skill published in the GitHub repository wardawgmalvicious/agent-config (1 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 1,393 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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