cx-create-dashboard
Build and deploy a Coralogix dashboard for a given service from its logs, spans, metrics, and service specs. Discovers telemetry via cx CLI commands, emits importable Coralogix JSON, verifies every PromQL and DataPrime query live through the `cx` CLI, and creates the dashboard via `cx dashboards create`. Use whenever the user asks to create, build, generate, or deploy a Coralogix dashboard, monitoring dashboard, or observability dashboard for a service, app, or pipeline.
93
92%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%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 is an excellent skill description that clearly articulates specific capabilities (telemetry discovery, query verification, dashboard creation via cx CLI), includes comprehensive trigger terms covering natural user phrasings, and explicitly states when to use the skill. The Coralogix-specific terminology and tooling references make it highly distinctive and unlikely to conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: discovers telemetry via cx CLI, emits importable Coralogix JSON, verifies PromQL and DataPrime queries live, creates dashboard via 'cx dashboards create'. Very detailed and actionable. | 3 / 3 |
Completeness | Clearly answers both 'what' (build/deploy Coralogix dashboards from logs/spans/metrics, discover telemetry, verify queries, create via CLI) and 'when' (explicit 'Use whenever the user asks to create, build, generate, or deploy a Coralogix dashboard...' clause). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms: 'create', 'build', 'generate', 'deploy', 'Coralogix dashboard', 'monitoring dashboard', 'observability dashboard', 'service', 'app', 'pipeline'. These are terms users would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche: specifically targets Coralogix dashboards, mentions the cx CLI, PromQL, DataPrime queries, and Coralogix JSON format. Very unlikely to conflict with generic monitoring or dashboard skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality, well-structured skill for a complex multi-step workflow. Its greatest strengths are the clear 7-phase workflow with explicit gates and validation checkpoints, highly actionable CLI commands and JSON templates, and excellent progressive disclosure to reference files. The main weakness is moderate verbosity—the skill could be tightened by removing some redundancy (duplicate reference listings) and compressing Phase 1's discovery steps, though the length is partially justified by the complexity of the task.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is generally efficient and avoids explaining basic concepts Claude already knows, but it's quite long (~300 lines) with some redundancy—reference tables appear twice (top and bottom), and some sections like Phase 1 could be tightened. The checklist format and tables are space-efficient, but the overall volume is high for what could be more compressed with better delegation to reference files. | 2 / 3 |
Actionability | Highly actionable throughout: concrete CLI commands (e.g., `cx metrics search --name '*<keyword>*'`, `cx dashboards create --from-file`), specific JSON structure templates, exact field paths (`$d.message`, `$l.applicationname`), widget-type selection tables, and copy-paste-ready bash commands. Phase 5 and Phase 7 give precise executable procedures. | 3 / 3 |
Workflow Clarity | Excellent 7-phase workflow with explicit sequencing constraints ('Don't jump to Phase 4 before the user approves Phase 3'), a progress checklist, validation gates (Phase 5 live-verification, Phase 6 structural self-check), feedback loops (retry budget, return to Phase 5 on deploy failure), and clear error handling ('surface it to the user with the CLI error verbatim'). The workflow is thorough and well-structured for a complex, multi-step process. | 3 / 3 |
Progressive Disclosure | The skill is structured as an overview with clear, well-signaled one-level-deep references to 8 specific reference files (dataprime-reference.md, promql-guidelines.md, widget-templates.md, verification.md, deploy.md, etc.). The reference table at the top provides task-based navigation, and inline references throughout point to the right file for detailed guidance. Content is appropriately split between the main skill and reference files. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- coralogix/cx-cli
- Commit
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- Reviewed
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