evernote-observability
Implement observability for Evernote integrations. Use when setting up monitoring, logging, tracing, or alerting for Evernote applications. Trigger with phrases like "evernote monitoring", "evernote logging", "evernote metrics", "evernote observability".
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill evernote-observability76
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
89%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 a well-structured skill description with excellent trigger term coverage and clear 'Use when' guidance. The main weakness is the lack of specific concrete actions - it describes the general category (observability) but not the specific capabilities (e.g., setting up Prometheus metrics, configuring OpenTelemetry, creating Grafana dashboards). The Evernote-specific focus provides strong distinctiveness.
Suggestions
Add specific concrete actions like 'configure structured logging', 'set up distributed tracing with correlation IDs', 'create metric dashboards', or 'define alert thresholds' to improve specificity
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (observability for Evernote integrations) and lists general actions (monitoring, logging, tracing, alerting), but doesn't specify concrete actions like 'configure log aggregation', 'set up distributed tracing', or 'create alert rules'. | 2 / 3 |
Completeness | Clearly answers both what (implement observability for Evernote integrations) and when (setting up monitoring, logging, tracing, or alerting) with explicit 'Use when' and 'Trigger with' clauses providing clear guidance. | 3 / 3 |
Trigger Term Quality | Explicitly lists natural trigger phrases users would say: 'evernote monitoring', 'evernote logging', 'evernote metrics', 'evernote observability'. These are realistic terms a user would naturally use when needing this skill. | 3 / 3 |
Distinctiveness Conflict Risk | The combination of 'Evernote' + 'observability/monitoring' creates a very specific niche. The explicit Evernote-prefixed trigger terms make it highly unlikely to conflict with general observability skills or other Evernote skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides highly actionable, production-ready observability code for Evernote integrations with excellent coverage of metrics, logging, tracing, and alerting. However, it suffers from being a monolithic document that would benefit significantly from splitting into referenced files, and lacks validation steps to verify the observability stack is working correctly.
Suggestions
Split the 7 implementation steps into separate referenced files (e.g., METRICS.md, LOGGING.md, TRACING.md) and keep SKILL.md as a concise overview with quick-start guidance
Add validation checkpoints after each step, such as 'Verify metrics endpoint returns data: curl localhost:9090/metrics | grep evernote_'
Include a troubleshooting section for common issues like metrics not appearing, traces not correlating, or alerts not firing
Add a quick-start section showing minimal setup (just metrics + health endpoint) before diving into the full stack
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is comprehensive but verbose - it includes full implementation code for multiple observability components that could be referenced externally. The metrics table and resources section add value, but the extensive code blocks (500+ lines) could be condensed or split into separate files. | 2 / 3 |
Actionability | Excellent actionability with fully executable JavaScript code, complete YAML alert configurations, and JSON dashboard definitions. All code is copy-paste ready with proper imports, exports, and configuration options. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered (1-7) covering the full observability stack, but there are no validation checkpoints or verification steps. Missing guidance on how to verify metrics are being collected correctly, logs are flowing, or alerts are firing as expected. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of code with no references to external files. The 7 major components (metrics, client, logging, tracing, health, alerts, dashboard) should each be in separate referenced files, with SKILL.md providing an overview and quick-start guidance. | 1 / 3 |
Total | 8 / 12 Passed |
Validation
72%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 8 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (597 lines); consider splitting into references/ and linking | Warning |
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 | 8 / 11 Passed | |
- Reviewed
Table of Contents
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