monitoring-error-rates
Monitor and analyze application error rates to improve reliability. Use when tracking errors in applications including HTTP errors, exceptions, and database issues. Trigger with phrases like "monitor error rates", "track application errors", or "analyze error patterns".
51
41%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/performance/error-rate-monitor/skills/monitoring-error-rates/SKILL.mdQuality
Discovery
82%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 solid description that clearly communicates both what the skill does and when to use it, with explicit trigger phrases. Its main weakness is that the capability actions are somewhat generic ('monitor and analyze') rather than listing specific concrete operations. The trigger terms are well-chosen and natural, though distinctiveness could be improved by more precisely scoping the skill's boundaries.
Suggestions
Replace generic verbs 'monitor and analyze' with more specific concrete actions, e.g., 'Calculate error rates, categorize exceptions by type, detect error spikes, and generate reliability reports'.
Add boundary language to improve distinctiveness, e.g., 'Not for infrastructure monitoring or uptime checks' to reduce potential overlap with related monitoring skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain (application error rates) and mentions some types of errors (HTTP errors, exceptions, database issues), but the actions are somewhat vague—'monitor and analyze' are broad verbs without listing specific concrete actions like 'generate error rate dashboards, set threshold alerts, categorize exceptions by type'. | 2 / 3 |
Completeness | Clearly answers both 'what' (monitor and analyze application error rates including HTTP errors, exceptions, database issues) and 'when' (explicit 'Use when' clause with trigger phrases like 'monitor error rates', 'track application errors', 'analyze error patterns'). | 3 / 3 |
Trigger Term Quality | Good coverage of natural trigger terms: 'monitor error rates', 'track application errors', 'analyze error patterns', plus specific error types like 'HTTP errors', 'exceptions', and 'database issues' that users would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | While it focuses on error rates specifically, there could be overlap with general monitoring/observability skills or application performance monitoring skills. The mention of 'database issues' could also conflict with database-specific skills. It's reasonably distinct but not perfectly carved out. | 2 / 3 |
Total | 10 / 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 content reads like a marketing overview or product specification rather than actionable instructions for Claude. It is entirely abstract with no executable code, no specific configurations, no concrete examples, and excessive verbosity explaining concepts Claude already understands. The content fails on all dimensions by describing what should happen rather than showing how to do it.
Suggestions
Replace the abstract 'Examples' section with concrete, executable code showing actual Prometheus alerting rules, Grafana dashboard JSON, or log parsing scripts that Claude can directly use or adapt.
Remove the 'Overview', 'How It Works', and 'When to Use This Skill' sections entirely—these waste tokens on information already captured in the skill description and frontmatter.
Add specific validation steps to the workflow, e.g., 'Run `promtool check rules alerts.yml` to validate alert syntax before deploying' with explicit error recovery loops.
Provide concrete configuration templates (e.g., a Prometheus recording rule for error rates, a sample alertmanager config) instead of generic bullet-point instructions.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive explanation of concepts Claude already knows. Sections like 'Overview', 'How It Works', 'When to Use This Skill', and 'Integration' are padded with generic descriptions that don't add actionable value. The entire file reads like a product description rather than executable instructions. | 1 / 3 |
Actionability | No concrete code, commands, or executable examples anywhere. The 'Instructions' section is a vague 6-step list with no specifics (e.g., 'Identify error sources by analyzing application architecture'). The examples describe what the skill 'will do' abstractly rather than showing how to do it with actual code or configurations. | 1 / 3 |
Workflow Clarity | The Instructions section lists steps but they are entirely abstract with no validation checkpoints, no specific commands, and no feedback loops. For a skill involving monitoring configuration (which can fail in many ways), there are no concrete verification steps. The Error Handling section is also generic bullet points without actionable recovery procedures. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no bundle files and no references to external resources for detailed content. All sections are inline at the same level of abstraction, and the 'Resources' section at the end lists generic categories rather than actual file references. No clear navigation structure. | 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 | |
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