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cekura-predefined-metrics

Use when the user asks "what predefined metrics are available", "which built-in metrics should I use", "what does CSAT measure", "how does hallucination detection work", "what's the difference between Interruption Score and AI Interrupting User", "which metrics are free", "which metrics need audio", "configure silence threshold", "set up sentiment metric", or any question about Cekura's out-of-the-box metrics. Covers the full catalog of predefined metrics — what each does, costs, constraints, configuration options, and when to use each one.

67

Quality

80%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./cekura/skills/cekura-predefined-metrics/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a well-structured reference skill that effectively catalogs Cekura's predefined metrics with clear tables, cost breakdowns, constraints, and a solid workflow. Its main weakness is the lack of concrete executable examples in the body — API calls, JSON payloads, and tool invocations are all deferred to reference files, reducing immediate actionability. Some sections (terminology, predefined vs custom comparison) add moderate verbosity without proportional value.

Suggestions

Add at least one concrete example in the body — e.g., a sample API call or tool invocation for toggling a metric on and attaching it to an evaluator, so the two-step process is immediately actionable.

Trim the 'Core Terminology' section to only non-obvious terms (e.g., keep 'Main agent' vs 'Testing agent' distinction but drop definitions of 'Predefined metric' and 'Custom metric' which are self-evident).

Include a minimal JSON configuration example inline (e.g., for silence_duration) rather than deferring all payload examples to the configuration guide.

DimensionReasoningScore

Conciseness

The skill is generally well-organized but includes some unnecessary sections like 'Core Terminology' definitions that Claude could infer, the 'Performing Platform Actions' preamble, and the 'Predefined vs Custom Metrics' section which is somewhat obvious. The catalog tables and configuration reference are dense and efficient, but the overall document could be tightened by ~20%.

2 / 3

Actionability

The skill provides concrete metric names, codes, configuration keys, and a clear two-step enablement process. However, it lacks executable code/command examples — no actual API call examples, no JSON payloads for configuration, and no tool invocation examples. It references these in external files (api-reference.md, configuration-guide.md) but the main body stays at the descriptive level.

2 / 3

Workflow Clarity

The six-step workflow is clearly sequenced with explicit validation ('Validate by running'), the two-step activation requirement is called out prominently with a warning about the consequence of missing either step, and Common Pitfalls serves as an effective error-recovery checklist. The baseline recommendation provides a clear starting point.

3 / 3

Progressive Disclosure

The skill is well-structured as an overview with clear one-level-deep references to three specific reference files (configuration-guide.md, api-reference.md, selection-by-use-case.md). The catalog tables provide enough detail to make decisions while deferring implementation specifics to reference files. Navigation between sections is logical and well-signaled.

3 / 3

Total

10

/

12

Passed

Description

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 strong description with excellent trigger term coverage and completeness. The 'Use when' clause is front-loaded with numerous realistic user queries, and the scope is clearly defined around Cekura's predefined metrics. The main weakness is that the 'what it does' portion is slightly generic — it describes coverage areas rather than listing specific concrete actions the skill performs.

DimensionReasoningScore

Specificity

The description names the domain (Cekura's predefined metrics) and mentions what it covers ('what each does, costs, constraints, configuration options, and when to use each one'), but the actual concrete actions are somewhat vague — it describes coverage areas rather than listing specific actions like 'list available metrics, explain metric configurations, compare metric differences.'

2 / 3

Completeness

Clearly answers both 'what' (covers the full catalog of predefined metrics — what each does, costs, constraints, configuration options, and when to use each one) and 'when' (explicit 'Use when' clause at the beginning with extensive trigger examples and a catch-all 'any question about Cekura's out-of-the-box metrics').

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms with many specific example queries users would actually say, including 'what predefined metrics are available', 'which metrics are free', 'which metrics need audio', 'configure silence threshold', 'set up sentiment metric', and domain-specific terms like 'CSAT', 'hallucination detection', 'Interruption Score'.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive — clearly scoped to Cekura's predefined/out-of-the-box metrics catalog, with specific product-specific terms like 'CSAT', 'Interruption Score', 'AI Interrupting User', and 'Cekura' that make it very unlikely to conflict with other skills.

3 / 3

Total

11

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
cekura-ai/cekura-skills
Reviewed

Table of Contents

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