cekura-metric-design
Use when the user asks to "create a metric", "write a metric", "design a metric", "build a metric for", "evaluate agent performance", "measure call quality", "track a KPI", "add a workflow metric", "improve my metric", "fix a metric", "debug metric results", "set up quality scoring", or "what metrics do I need". Also relevant when discussing LLM judge prompts, custom code metrics, evaluation triggers, VALID_SKIP patterns, section extraction, or metric best practices for Cekura voice AI agents. Covers both creating new metrics and reviewing, iterating on, or troubleshooting existing ones.
81
71%
Does it follow best practices?
Impact
98%
1.38xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./cekura/skills/cekura-metric-design/SKILL.mdSecurity
1 medium severity finding. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.90). The skill explicitly instructs fetching and ingesting real, user-generated call transcripts from the Cekura API (see "The Metric Creation Workflow" step 2 and use of {{transcript}} / {{transcript_json}} in prompts), and those transcripts are read by LLM judge prompts and custom_code to make evaluation and tooling decisions—exposing the agent to untrusted third-party content that can materially influence actions.
- Repository
- cekura-ai/cekura-skills
- Commit
24ad1d0
- Audited
- Security analysis
Is this your skill?
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