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azure-kusto

Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection.

Quality

85%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable, with executable KQL examples for every common case, precise MCP tool parameters, and a complete CLI fallback path, and its core workflow is clearly sequenced with scattered but real error-recovery guidance. It is held back by token inefficiency (redundant overview/capabilities/best-practices sections and padded use-case/result-format material) and by inlining everything — including a CLI command reference — in one long file instead of offloading detail to reference files.

Suggestions

Merge the duplicate "KQL Best Practices" and "Best Practices" sections, delete the redundant Overview paragraph and "Key capabilities" list (they duplicate the intro and later sections), and cut "Result Format" and "Use Cases" to reclaim token budget in the two lowest-value areas.

Move the Azure CLI fallback command reference and extended troubleshooting into a references/ file (e.g., references/cli-fallback.md) and link to it from SKILL.md, keeping the main file a lean overview plus query patterns.

Integrate validation checkpoints directly into the Core Workflow steps (e.g., "verify the table exists via kusto_table_schema_get before querying" and "confirm non-empty results before reporting findings") so error handling is procedural rather than only in the troubleshooting section.

DimensionReasoningScore

Conciseness

The pattern examples, tool tables, and CLI fallback are lean, but the file carries a redundant intro paragraph plus Overview paragraph ("Execute KQL queries and manage Azure Data Explorer resources..." followed by "This skill enables querying and managing Azure Data Explorer..."), a "Key capabilities" list duplicating later sections, two overlapping "KQL Best Practices" and "Best Practices" sections, and padding such as "Result Format" and "Use Cases". This fits anchor 3 (mostly efficient, some unnecessary explanation that could be tightened) better than anchor 2, since the majority of sections are dense and useful, but the volume of padded sections keeps it below anchor 4.

3 / 5

Actionability

The body provides copy-paste-ready KQL for patterns 1-4 and 6 (including the union workspace('ws1')/workspace('ws2') example), a named MCP tool table with required parameters per operation, and complete Azure CLI fallback commands with full flag syntax plus an executable az rest query template. Specific examples cover the common cases as anchor 5 requires; anchor 4's "minor gaps" only marginally applies (Pattern 5 names its tool without a call example), so the common-case coverage keeps it at 5.

5 / 5

Workflow Clarity

The 4-step Core Workflow (Discover Resources, Explore Schema, Query Data, Analyze Results) is clearly sequenced, and error-recovery feedback exists via "When to Fallback" conditions, the "Common Issues" fix list, and Pattern 6's instruction to only report "not found" after all candidates are checked. It fits anchor 4 rather than 5 because validation is not integrated as explicit checkpoints within the workflow steps themselves, and it stays above anchor 3 because feedback loops for the database operations (fallback + troubleshooting) are present, so the cap-at-3 note does not apply.

4 / 5

Progressive Disclosure

This is a single 214-line SKILL.md with no bundle files and good section headers, but content that clearly belongs in separate reference files is inlined: the ~35-line CLI fallback command reference, the "Use Cases" section, and "Result Format". It fits anchor 3 (some structure, content that should be separate is inline) — better organized than anchor 2's minimal structure, but the under-50-lines exception for scoring 5 does not apply and nothing is offloaded.

3 / 5

Total

15

/

20

Passed

Description

91%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that precisely names the domain and query language, answers both what and when explicitly, and supplies a comprehensive trigger-term list including all service synonyms. Its only weaknesses are a slightly thin action list relative to the body's full capabilities and mild overlap risk from generic phrases like "log analytics" and "time series data".

DimensionReasoningScore

Specificity

"Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis" names the domain precisely with several concrete capability areas (log analytics, telemetry, time series analysis), falling between anchor 3 (1-2 concrete actions, not comprehensive) and anchor 4 (several specific actions, minor gaps). It sits noticeably above the midpoint because the domain and language are exact, but stays below anchor 5 since distinct actions are limited to query/analyze and the body's schema-exploration and resource-management capabilities are absent.

4 / 5

Completeness

It explicitly answers what ("Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis") and when (a dedicated WHEN clause with eight concrete trigger phrases), matching anchor 5. It is above anchor 4 because the 'when' is fully explicit, not merely present-but-imprecise.

5 / 5

Trigger Term Quality

"WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection" comprehensively covers the natural terms a user would say, including all service synonyms (Kusto, ADX, Azure Data Explorer) and the query language (KQL). This matches anchor 5's comprehensive synonym coverage; anchor 4's "a few natural terms missing" is a worse fit because no common phrasing for this domain is absent.

5 / 5

Distinctiveness Conflict Risk

The niche is clear and mostly distinct via KQL/Kusto/ADX/Azure Data Explorer triggers, but "log analytics" and "time series data" are generic enough to also match an Azure Monitor Log Analytics skill or a generic analytics skill — minor overlap risk with closely related skills per anchor 4, not the minimal-conflict anchor 5.

4 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

microsoft/azure-skills

Path

.github/plugins/azure-skills/skills/azure-kusto/SKILL.md

Reviewed

Table of Contents

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