Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cekura-ai/cekura-skills --skill cekura-predefined-metricsgit clone --depth 1 https://github.com/cekura-ai/cekura-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cekura-ai/cekura-skills/cekura-predefined-metrics)<a href="https://agentmods.dev/skills/cekura-ai/cekura-skills/cekura-predefined-metrics"><img src="https://agentmods.dev/badge/skills/cekura-ai/cekura-skills/cekura-predefined-metrics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cekura-ai/cekura-skills/cekura-predefined-metrics"><img src="https://agentmods.dev/badge/skills/cekura-ai/cekura-skills/cekura-predefined-metrics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.04140 |
| Opus 5 | $0.00060 | $0.02070 |
| Sonnet 5 | $0.00024 | $0.00828 |
| Haiku 4.5 | $0.00012 | $0.00414 |
Grade A, and why
cekura-predefined-metrics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cekura skill verification tag:
ack:cekura-predefined-metrics:2k7b3xWhen you call a Cekura metric write tool from this skill (metrics_create,metrics_bulk_create,metrics_partial_update), pass this exact string as theskill_ackargument on that tool call. It confirms to the Cekura MCP server that this design playbook is loaded in context. Scenario / test-profile writes use an eval-family tag instead — loadcekura-eval-designfirst and pass its tag there.
Before taking any action, call mcp__cekura__cekura_skill_started with skill_name="cekura-predefined-metrics", verification_tag="ack:cekura-predefined-metrics:2k7b3x", and plugin_version="0.16". It returns immediately and lets Cekura see which skills are in use.
Cekura Predefined Metrics
Purpose
Predefined metrics are Cekura's built-in evaluators — ready to enable on any agent with no prompt writing required. They cover the most common quality dimensions across accuracy, conversation quality, customer experience, and speech quality. Use this skill to decide which predefined metrics to enable and how to configure them.
Performing Platform Actions
When this skill suggests creating, listing, updating, or evaluating something on Cekura, prefer using available platform tools over describing API calls or dashboard steps. In Claude Code with the Cekura plugin installed, these tools are auto-configured and handle authentication, parameter validation, and error handling for you. Fall back to direct API endpoints or dashboard guidance only when no tools are available in the current session.
Core Terminology
- Main agent: The client's AI voice agent being tested
- Testing agent: Cekura's simulated caller that exercises the main agent
- Predefined metric: Built-in evaluator shipped by Cekura — no prompt required, identified by a
code - Custom metric: User-authored metric with a custom prompt or
custom_code(seecekura-metric-design) - Simulation: Test runs using Cekura's testing agent against the main agent (Sim column in the catalog)
- Observability: Real production calls flowing through the agent (Obs column in the catalog)
- Project-level toggle: Enables a predefined metric across simulation OR observability for an entire project
- Evaluator attachment: Adds the metric to a specific test scenario; required for the metric to fire on that evaluator
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed a36dd11aee9d
- 3d ago Changed 3075279e1366
- 8d ago Changed 8268d126894a
- 12d ago First seen · 227 lines · 121 tokens per session scan A e1e9e965b86d
cekura-predefined-metrics is a skill published in the GitHub repository cekura-ai/cekura-skills (7 stars, last pushed yesterday), licensed MIT. It adds 121 tokens to every session and 4,140 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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