prometheus-configuration

Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.

1.22x

Quality

—

Does it follow best practices?

Impact

94%

1.22x

Average score across 3 eval scenarios

Securityby

Advisory

Suggest reviewing before use

Quality

Content

65%

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 complete, executable Prometheus configuration, rules, and validation commands. Its weaknesses are conciseness (redundant inline config duplicated across sections plus an unnecessary architecture diagram), workflow clarity (validation exists but is not woven into an explicit sequenced workflow with feedback loops), and progressive disclosure (referenced bundle files are missing while their content stays inline).

Suggestions

Remove the duplicated inline prometheus.yml content that overlaps the dedicated Scrape Configurations, Recording Rules, and Alert Rules sections, or move the full config into the referenced assets/prometheus.yml.template and keep only a concise skeleton inline.

Frame the setup as an explicit numbered workflow (install → configure → define rules → validate → troubleshoot) with promtool validation as a checkpoint and a fix-and-re-validate feedback loop.

Create the referenced bundle files (references/scrape-configs.md, references/recording-rules.md, scripts/validate-prometheus.sh, assets/prometheus.yml.template) so the signaled navigation resolves to real content, or drop references to files that do not exist.

Dimension	Reasoning	Score
Conciseness	The body is mostly task-relevant config rather than concept fluff, but it is verbose: a full inline prometheus.yml duplicates content also shown in the dedicated Scrape Configurations, Recording Rules, and Alert Rules sections, and an ASCII architecture diagram explains concepts Claude already knows. It is not the level-3 lean ideal, yet not padded enough for level 1.	2 / 3
Actionability	Provides fully executable, copy-paste-ready guidance throughout — a complete helm install command, docker-compose.yml, prometheus.yml, recording/alert rule YAML, promtool check config/check rules/query commands, and curl API queries. This matches the anchor for fully executable code and commands.	3 / 3
Workflow Clarity	The content is organized into logical topic sections and includes a dedicated Validation section with promtool check config and check rules, but it is not framed as an explicit numbered end-to-end sequence with feedback loops (e.g., if validation fails, fix and re-validate). Checkpoints exist but are implicit rather than integrated into a sequenced workflow, matching the anchor for steps present but checkpoints missing or implicit.	2 / 3
Progressive Disclosure	References are clearly signaled one-level-deep ("Reference: See ...") and listed in a Reference Files section, but the referenced bundle files (assets/prometheus.yml.template, references/scrape-configs.md, references/recording-rules.md, scripts/validate-prometheus.sh) do not exist on disk, and the large config/rules content that should be split out remains inline and duplicated. This matches the anchor for some structure with content that should be separate kept inline.	2 / 3
	Total	9 / 12 Passed

Description

85%

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

The description is specific, complete, and distinct: it names Prometheus and concrete actions, and provides an explicit "Use when..." clause covering both what and when. Its only weakness is trigger-term coverage, which captures the core terms but misses several natural synonyms a user might say.

Dimension	Reasoning	Score
Specificity	Names the concrete domain (Prometheus) and lists multiple specific actions — "metric collection, storage, and monitoring", "implementing metrics collection", "configuring alerting systems" — matching the anchor for listing several specific concrete actions.	3 / 3
Completeness	Explicitly answers both what ("Set up Prometheus for comprehensive metric collection, storage, and monitoring...") and when ("Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems"), matching the anchor for clearly answering both with explicit triggers.	3 / 3
Trigger Term Quality	Includes natural terms a user would say ("Prometheus", "metrics collection", "monitoring infrastructure", "alerting systems") but omits common variations like scraping, dashboards, or recording rules, matching the anchor for some relevant keywords with missing variations.	2 / 3
Distinctiveness Conflict Risk	Naming a specific tool (Prometheus) with targeted monitoring/metrics/alerting triggers gives a clear niche unlikely to conflict with unrelated skills, matching the anchor for a clear niche with distinct triggers.	3 / 3
	Total	11 / 12 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
referenced_paths_exist	Referenced path issues: 8 missing	Warning

	Total	15 / 16 Passed

Repository: Dicklesworthstone/pi_agent_rust
Commit: e9f9b67

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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