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cekura-personality-design

Use when the user asks to "create a personality", "make a custom personality", "add a caller persona", "fork a personality", "change the testing agent's voice", "test a different accent", "add an Indian/British/Spanish accent caller", "make the caller interrupt more", "add background noise", "make it speak slower", "the testing agent keeps asking if I'm still there", "simulate a bad connection", or "which personality should I use". Also for questions about the difference between a personality and an evaluator, why instructions like "speak with an accent" or "be interruptive" don't change how the caller sounds, and why a personality's accent field cannot be set directly. Covers choosing, forking, creating and patching personalities — the simulated caller's voice, language, timing and audio layer.

72

Quality

90%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

85%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, domain-specific playbook: it leads with the highest-cost failure mode (personality vs. evaluator boundary), gives concrete tool-level guidance with valid values and validation checkpoints, and splits detail into two appropriate reference files. The only weaknesses are repetition of the boundary lesson and the absence of one fully assembled example call in the body.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's competence — no generic explainer padding, and tables carry settings compactly — but the core 'evaluator instructions cannot change the audio' point is repeated across the Boundary section, the Accent section, the duration-routing table, and the Pitfalls list, so a few passages could be trimmed.

4 / 5

Actionability

Concrete tool names with parameters, valid values, and defaults throughout (`personalities_list` with `language=<code>`, `voice_id`+`provider` pairing rules, `speed` `0.8`–`1.2`, `idle_timeout_seconds` default 10, dashboard URL pattern), but no single assembled end-to-end example call in the body — the fork/patch block is schematic — leaving a minor gap.

4 / 5

Workflow Clarity

The Choose→Fork→Create decision procedure is ordered with a stop-at-first-fit rule, and the 9-step Creation Workflow has an explicit validation checkpoint (step 7 'Verify by reading back — `personalities_retrieve`'), confirm-before-fork guards for the fan-out (batch) patch effect, error-recovery notes for blank `accent`, and a Pitfalls checklist — matching the anchor with validation steps, recovery guidance, and a checklist.

5 / 5

Progressive Disclosure

Two references (`references/personality-vs-evaluator.md`, `references/voice-and-accent.md`) are clearly signaled with descriptions of their content, verified to exist as real one-level-deep files with no nested references, and the Next Steps section aids navigation; the body stays a decision-level overview with detail pushed to the references.

5 / 5

Total

18

/

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 strong description: explicit what and when, exceptional natural-language trigger coverage in third person, and a well-delineated niche. Its only limitations are that the what-clause enumerates actions without further detail and it shares an ecosystem boundary with a sibling evaluator-design skill.

DimensionReasoningScore

Specificity

The what-clause names the domain and four concrete actions — 'Covers choosing, forking, creating and patching personalities — the simulated caller's voice, language, timing and audio layer' — matching the anchor for several specific actions with minor gaps in coverage (e.g., listing personalities and voice-catalog lookup are not named as actions).

4 / 5

Completeness

Both what and when are explicit and concrete: an extensive 'Use when the user asks to…' trigger list followed by 'Covers choosing, forking, creating and patching personalities…', directly matching the anchor for explicit what-and-when with concrete trigger phrases.

5 / 5

Trigger Term Quality

Thirteen quoted natural user phrasings with synonyms and variations — 'create a personality', 'make a custom personality', 'fork a personality', 'add an Indian/British/Spanish accent caller', 'make the caller interrupt more', 'simulate a bad connection', 'which personality should I use' — plus symptom-style triggers; comprehensive natural-term coverage.

5 / 5

Distinctiveness Conflict Risk

The Cekura personality/voice-layer niche is clear with distinct triggers, but the adjacent sibling skill `cekura-eval-design` overlaps (the description itself must arbitrate the personality-vs-evaluator boundary), giving minor overlap risk with a closely related skill rather than minimal conflict risk.

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

cekura-ai/cekura-skills

Path

cekura/skills/cekura-personality-design/SKILL.md

Reviewed

Table of Contents

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