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.
53
58%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/observability-monitoring/skills/prometheus-configuration/SKILL.mdQuality
Discovery
67%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 structurally sound with a clear 'Use when' clause and identifies the core domain (Prometheus monitoring). However, it lacks specific concrete actions beyond high-level categories and could better differentiate itself from other monitoring tool skills. Adding more specific capabilities and natural trigger terms would strengthen it.
Suggestions
Add more specific concrete actions such as 'configure scrape targets, write PromQL queries, set up Alertmanager rules, define recording rules, configure exporters'.
Include additional natural trigger terms users might say, such as 'PromQL', 'scrape config', 'node_exporter', 'time series database', or 'prometheus.yml'.
Clarify distinctiveness by specifying this is specifically for Prometheus (not Grafana, Datadog, etc.) in the 'Use when' clause, e.g., 'Use when the user mentions Prometheus, PromQL, or needs a pull-based metrics system'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Prometheus, monitoring) and some actions (metric collection, storage, monitoring, alerting), but doesn't list multiple concrete specific actions like configuring scrape targets, writing PromQL queries, setting up Alertmanager rules, or creating recording rules. | 2 / 3 |
Completeness | Clearly answers both 'what' (set up Prometheus for metric collection, storage, and monitoring) and 'when' (explicit 'Use when' clause covering metrics collection, monitoring infrastructure, and alerting systems). | 3 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Prometheus', 'metrics collection', 'monitoring infrastructure', and 'alerting systems', but misses common user variations like 'PromQL', 'scrape config', 'Grafana', 'exporters', 'node_exporter', 'time series', or '.yml configuration'. | 2 / 3 |
Distinctiveness Conflict Risk | Mentioning 'Prometheus' specifically helps distinguish it, but the broad terms 'monitoring infrastructure' and 'alerting systems' could overlap with skills for Grafana, Datadog, Nagios, or other monitoring tools. | 2 / 3 |
Total | 9 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill excels at actionability with comprehensive, executable configuration examples covering installation, scraping, recording rules, and alerting. However, it is excessively verbose with redundant scrape configuration examples and content Claude already knows (architecture overview, best practices list). The workflow lacks integrated validation checkpoints, and referenced bundle files don't exist, undermining the progressive disclosure structure.
Suggestions
Cut the content by ~50%: remove the architecture diagram, 'When to Use' list, 'Best Practices' bullet list, and deduplicate scrape config examples — keep only the comprehensive prometheus.yml and one service discovery variant.
Integrate validation steps into the workflow: after writing prometheus.yml, immediately show 'promtool check config prometheus.yml' as a required checkpoint before deploying, with error recovery guidance.
Either provide the referenced bundle files (assets/prometheus.yml.template, references/scrape-configs.md, etc.) or remove the references — currently they point to nonexistent files.
Move the detailed Kubernetes SD config and TLS scrape examples into a referenced file to keep the main skill focused on the core setup workflow.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~300+ lines, with significant redundancy. The scrape configurations section repeats patterns already shown in the main prometheus.yml. The architecture diagram, 'When to Use' list, and 'Best Practices' bullet list are all things Claude already knows. The Kubernetes SD config appears twice with slight variations. | 1 / 3 |
Actionability | The skill provides fully executable, copy-paste ready configurations throughout — complete Helm commands, Docker Compose files, prometheus.yml configs, recording rules, alert rules, and validation commands. All code blocks are concrete and specific. | 3 / 3 |
Workflow Clarity | There is a validation section with promtool commands, but it's disconnected from the workflow — it appears as a standalone section rather than integrated as checkpoints within the setup process. There's no explicit sequence like 'write config → validate → deploy → verify targets' with feedback loops for error recovery. | 2 / 3 |
Progressive Disclosure | References to external files exist (assets/prometheus.yml.template, references/scrape-configs.md, references/recording-rules.md, scripts/validate-prometheus.sh) but no bundle files are provided, meaning these references are broken. The main file also contains too much inline detail that should be in those referenced files, defeating the purpose of progressive disclosure. | 2 / 3 |
Total | 8 / 12 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 — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- wshobson/agents
- Commit
34632bc
- Reviewed
Table of Contents
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