aggregating-performance-metrics

tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill aggregating-performance-metrics

Aggregate and centralize performance metrics from applications, systems, databases, caches, and services. Use when consolidating monitoring data from multiple sources. Trigger with phrases like "aggregate metrics", "centralize monitoring", or "collect performance data".

54%

Overall

Validation — 81%

Implementation — 20%

Activation — 82%

SKILL.md

Review

Evals

Validation

81%

Warnings & errors only

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
metadata_version	'metadata' field is not a dictionary	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Implementation

20%

This skill is primarily descriptive rather than instructive, explaining what Claude 'will do' instead of providing actionable guidance. It lacks any concrete code examples, configuration snippets, or executable commands for metrics aggregation tools. The content would benefit greatly from actual Prometheus/StatsD/CloudWatch configuration examples and specific implementation details.

Suggestions

Replace abstract descriptions with concrete, executable configuration examples (e.g., actual prometheus.yml scrape configs, StatsD client code, CloudWatch metric definitions)

Remove meta-commentary about what Claude will do and replace with direct instructions and code snippets

Add specific metrics naming convention examples with actual metric names rather than just describing the concept

Include validation steps in the workflow (e.g., 'Test scrape endpoint: curl localhost:9090/metrics', 'Verify metric ingestion: promql query')

Dimension	Reasoning	Score
Conciseness	Extremely verbose with unnecessary explanations of what Claude will do ('Claude assists', 'Claude helps', 'Claude guides'). The Overview section explains obvious benefits, and much content describes rather than instructs. Significant padding throughout.	1 / 3
Actionability	No concrete code, commands, or executable examples. Everything is abstract description ('Guide the user', 'Help configure'). No actual Prometheus configs, scrape configurations, or dashboard definitions provided despite claiming to help with these tasks.	1 / 3
Workflow Clarity	The Instructions section provides a numbered sequence of steps, but they are vague ('Design consistent metrics naming convention') with no validation checkpoints. No feedback loops for error recovery despite dealing with multi-system integration.	2 / 3
Progressive Disclosure	Content is organized into sections but is monolithic with no references to external files for detailed configurations, examples, or tool-specific guides. The Resources section lists external docs but provides no links or paths.	2 / 3
	Total	6 / 12 Passed

Activation

82%

This is a solid description with explicit trigger guidance and clear 'when to use' clauses. The main weakness is that the capabilities described are somewhat high-level ('aggregate and centralize') without specifying concrete actions, and the broad scope covering many source types could create overlap with more specialized monitoring skills.

Suggestions

Add more specific concrete actions beyond 'aggregate and centralize', such as 'create unified dashboards', 'correlate cross-service metrics', or 'configure metric collectors'

Consider narrowing the scope or adding distinguishing details about what makes this different from individual monitoring tools (e.g., 'for cross-service correlation' or 'when metrics span multiple systems')

Dimension	Reasoning	Score
Specificity	Names the domain (performance metrics) and lists sources (applications, systems, databases, caches, services), but the actions 'aggregate and centralize' are somewhat generic and don't describe specific concrete operations like 'create dashboards', 'set up alerts', or 'configure collectors'.	2 / 3
Completeness	Clearly answers both what (aggregate and centralize performance metrics from various sources) and when (consolidating monitoring data, with explicit trigger phrases). The 'Use when' and 'Trigger with' clauses provide explicit guidance.	3 / 3
Trigger Term Quality	Includes explicit trigger phrases ('aggregate metrics', 'centralize monitoring', 'collect performance data') that users would naturally say. Also mentions relevant domain terms like 'performance metrics', 'monitoring data', and 'multiple sources'.	3 / 3
Distinctiveness Conflict Risk	While focused on metrics aggregation, it could potentially overlap with general monitoring skills, observability tools, or individual database/cache monitoring skills. The scope is broad ('applications, systems, databases, caches, and services') which increases conflict risk.	2 / 3
	Total	10 / 12 Passed

Reviewed

15 days ago

Table of Contents

Validation Implementation Activation

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