pipeline-monitoring-setup
Pipeline Monitoring Setup - Auto-activating skill for Data Pipelines. Triggers on: pipeline monitoring setup, pipeline monitoring setup Part of the Data Pipelines skill category.
33
0%
Does it follow best practices?
Impact
96%
1.01xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/11-data-pipelines/pipeline-monitoring-setup/SKILL.mdQuality
Discovery
0%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is essentially a title restated with no substantive content. It lacks concrete actions, meaningful trigger terms, explicit 'when to use' guidance, and any distinguishing details that would help Claude select it appropriately from a pool of skills.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Configures monitoring dashboards, sets up pipeline health checks, defines alerting rules for data pipeline failures and latency.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about monitoring data pipelines, setting up pipeline alerts, tracking pipeline health, or configuring observability for ETL/ELT workflows.'
Include varied natural keywords users might say, such as 'pipeline alerts', 'pipeline health', 'data pipeline observability', 'ETL monitoring', 'pipeline failure detection', to improve trigger term coverage and distinctiveness.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the domain ('pipeline monitoring setup') but lists no concrete actions. There are no specific capabilities like 'configure alerts', 'set up dashboards', 'define health checks', etc. | 1 / 3 |
Completeness | The description fails to clearly answer 'what does this do' beyond restating the title, and there is no explicit 'Use when...' clause explaining when Claude should select this skill. The 'Triggers on' line is just a duplicate of the title, not meaningful trigger guidance. | 1 / 3 |
Trigger Term Quality | The trigger terms are just 'pipeline monitoring setup' repeated twice — no natural variations users might say like 'monitor data pipeline', 'pipeline alerts', 'pipeline health checks', 'observability', 'pipeline dashboards', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely generic — 'pipeline monitoring setup' could overlap with general DevOps monitoring skills, observability tools, or other data pipeline skills. There is nothing to distinguish it from related skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a placeholder or template with no substantive content. It contains only self-referential descriptions of what it claims to do without any actual instructions, code, configurations, or concrete guidance for pipeline monitoring setup. It provides no value beyond what the skill's title already communicates.
Suggestions
Add concrete, executable examples for setting up pipeline monitoring (e.g., Airflow health checks, Prometheus metrics exporters, alerting rules in YAML/JSON).
Define a clear multi-step workflow for implementing monitoring on a data pipeline, including validation steps (e.g., verify metrics are being scraped, test alert firing).
Remove all meta-description sections ('Purpose', 'When to Use', 'Example Triggers', 'Capabilities') and replace with actionable technical content—specific tools, configurations, and code snippets.
Add references to supplementary files for advanced topics (e.g., ALERTING.md for alert configuration, DASHBOARDS.md for Grafana setup) to support progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely filler and meta-description. It explains what the skill does in abstract terms without providing any actual technical content. Every section restates the same vague idea ('pipeline monitoring setup') without adding substance. | 1 / 3 |
Actionability | There is zero concrete guidance—no code, no commands, no specific tools, no configuration examples, no architecture patterns. The skill describes rather than instructs, offering only vague promises like 'provides step-by-step guidance' without actually delivering any. | 1 / 3 |
Workflow Clarity | No workflow is defined at all. There are no steps, no sequence, no validation checkpoints. The 'Capabilities' section claims step-by-step guidance but none is present. | 1 / 3 |
Progressive Disclosure | The content is a flat, monolithic block of meta-descriptions with no references to detailed materials, no links to related files, and no structured navigation to deeper content. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
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- Reviewed
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