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 autohandai/community-skills --skill azure-kustogit clone --depth 1 https://github.com/autohandai/community-skillsWrote 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/autohandai/community-skills/azure-kusto)<a href="https://agentmods.dev/skills/autohandai/community-skills/azure-kusto"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/azure-kusto/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/autohandai/community-skills/azure-kusto"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/azure-kusto.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 | $0.00086 | $0.02044 |
| Opus 5 | $0.00043 | $0.01022 |
| Sonnet 5 | $0.00017 | $0.00409 |
| Haiku 4.5 | $0.00009 | $0.00204 |
Grade A, and why
azure-kusto 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 9d 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.
This is a copy
97% identical to azure-kusto — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Data Explorer (Kusto) Query & Analytics
Execute KQL queries and manage Azure Data Explorer resources for fast, scalable big data analytics on log, telemetry, and time series data.
Skill Activation Triggers
Use this skill immediately when the user asks to:
- "Query my Kusto database for [data pattern]"
- "Show me events in the last hour from Azure Data Explorer"
- "Analyze logs in my ADX cluster"
- "Run a KQL query on [database]"
- "What tables are in my Kusto database?"
- "Show me the schema for [table]"
- "List my Azure Data Explorer clusters"
- "Aggregate telemetry data by [dimension]"
- "Create a time series chart from my logs"
Key Indicators:
- Mentions "Kusto", "Azure Data Explorer", "ADX", or "KQL"
- Log analytics or telemetry analysis requests
- Time series data exploration
- IoT data analysis queries
- SIEM or security analytics tasks
- Requests for data aggregation on large datasets
- Performance monitoring or APM queries
Overview
This skill enables querying and managing Azure Data Explorer (Kusto), a fast and highly scalable data exploration service optimized for log and telemetry data. Azure Data Explorer provides sub-second query performance on billions of records using the Kusto Query Language (KQL).
Key capabilities:
- Query Execution: Run KQL queries against massive datasets
- Schema Exploration: Discover tables, columns, and data types
- Resource Management: List clusters and databases
- Analytics: Aggregations, time series, anomaly detection, machine learning
Core Workflow
- Discover Resources: List available clusters and databases in subscription
- Explore Schema: Retrieve table structures to understand data model
- Query Data: Execute KQL queries for analysis, filtering, aggregation
- Analyze Results: Process query output for insights and reporting
Query Patterns
Pattern 1: Basic Data Retrieval
Fetch recent records from a table with simple filtering.
Example KQL:
Events
| where Timestamp > ago(1h)
| take 100
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.
- 9d ago First seen · 232 lines · 86 tokens per session scan A bb2e17c37564
azure-kusto is a skill published in the GitHub repository autohandai/community-skills (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 86 tokens to every session and 2,044 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to azure-kusto, differing in 5 lines, and is treated as a copy.
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