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cekura-eval-design

Use when the user asks to "generate (test) scenarios", "generate evaluators", "create an evaluator", "create evals", "create a scenario", "write a test scenario", "design a test case", "test my agent", "build eval coverage", "plan a test suite", "create red team tests", "set up test profiles", "configure conditional actions", "build a deterministic test", "design an IVR test", "write a unit test for a voice agent", "build a regression test", "scripted scenario", "structured evaluator", or "run evals". Also for CHANGING existing evaluators — "update an evaluator", "improve my evals", "make these evaluators stricter", "add a DTMF step", "fix the expected outcome", "attach metrics to these" — and for debugging how the testing agent speaks: "why did it read the number as a word", "make it spell digits", "wrong language". Covers evaluator design and review, coverage, test profiles, mock-tool data, conditional actions, and red-team / edge-case practice.

68

Quality

82%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

73%Weight 40%Scale 1-5

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

A well-structured, highly actionable instruction skill with strong workflow sequencing and explicit validation/feedback loops for batch and destructive operations. Its weaknesses are length (several sections could be tightened or offloaded to references) and three referenced example files (examples/*.md) that do not exist in the bundle.

Suggestions

Tighten or move the large Mode routing table and the exhaustive CA tag table into references/conditional-actions.md, keeping only the decision rule and the most common tags inline to improve conciseness.

Create the three missing examples/workflow-eval.md, examples/red-team-eval.md, and examples/csv-eval-creation.md (or remove the dangling references) so every cited bundle path resolves.

Add one complete, runnable generate-call JSON payload alongside the CA payload so the most common write path (generation) is as copy-paste-ready as the direct-create path.

DimensionReasoningScore

Conciseness

The body is information-dense and avoids explaining concepts Claude already knows, but at ~440 lines / ~7600 words many sections (the long Mode table, the dense Step-writing rules, the exhaustive tag table) run long and could be tightened or pushed to references; it sits at 'mostly efficient but could be tightened' rather than lean.

3 / 5

Actionability

Provides a complete copy-paste-ready CA JSON payload, concrete field tables, exact tag syntax with ranges, and explicit self-check checklists; the only gaps are a few placeholder values like "agent": 123 and the absence of a runnable generate-call example payload, leaving it just short of fully executable across every common case.

4 / 5

Workflow Clarity

A clear 7-step workflow with explicit validation checkpoints (read the agent, one consolidated checkpoint, self-checks before every create, always-poll post-generation reconciliation, read-back diff on updates) and feedback loops (stall/freeze retry, fix-and-revalidate on outcomes), satisfying the explicit-validation anchor for batch/destructive operations.

5 / 5

Progressive Disclosure

Good structure with a curated overview plus clearly signaled one-level-deep references (references/*.md enumerated with summaries); however the three examples/*.md files named at the end do not exist in the bundle, and some detail (e.g. the full tag table, the large mode-routing table) arguably belongs in references rather than inline, leaving minor organization gaps.

4 / 5

Total

16

/

20

Passed

Description

91%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A dense, trigger-rich description that explicitly covers both what the skill does and when to use it, with extensive natural user phrasings for creating and modifying evaluators. The main weakness is that capabilities are listed as user quotes rather than a clean action enumeration, which slightly blurs specificity and leaves minor overlap with sibling Cekura skills.

DimensionReasoningScore

Specificity

Names the domain (evaluator/scenario design for AI voice/chat agents) and several concrete actions (generate scenarios, create evaluators, set up test profiles, configure conditional actions, attach metrics, fix expected outcomes), but the action list is framed as user request phrasings rather than a crisp enumeration of capabilities, leaving minor coverage gaps.

4 / 5

Completeness

Explicitly answers both 'what' (evaluator design and review, coverage, test profiles, mock-tool data, conditional actions, red-team/edge-case practice) and 'when' (a long 'Use when...' clause with concrete trigger phrases for creating and changing evaluators), matching the both-what-and-when anchor.

5 / 5

Trigger Term Quality

Comprehensive natural trigger coverage including common variations and synonyms — 'generate (test) scenarios', 'create an evaluator', 'design a test case', 'build eval coverage', 'run evals', 'make it spell digits' — far exceeding the synonym-and-extension anchor.

5 / 5

Distinctiveness Conflict Risk

It carves a clear niche (Cekura evaluator/test-scenario design, distinct from metrics) with minimal conflict risk, but broad quality-probing phrases like 'test my agent' and 'improve my evals' could overlap with adjacent Cekura skills (cekura-metric-design, cekura-self-improving-agent) named in the body, so it is not perfectly conflict-free.

4 / 5

Total

18

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
cekura-ai/cekura-skills
Reviewed

Table of Contents

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.