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-onboardinggit 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-onboarding)<a href="https://agentmods.dev/skills/cekura-ai/cekura-skills/cekura-onboarding"><img src="https://agentmods.dev/badge/skills/cekura-ai/cekura-skills/cekura-onboarding/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-onboarding"><img src="https://agentmods.dev/badge/skills/cekura-ai/cekura-skills/cekura-onboarding.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 | $0.00156 | $0.01450 |
| Opus 5 | $0.00078 | $0.00725 |
| Sonnet 5 | $0.00031 | $0.00290 |
| Haiku 4.5 | $0.00016 | $0.00145 |
Grade A, and why
cekura-onboarding 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 3d ago.
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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cekura Platform Onboarding
Walk a new user from account to their first verified result — a completed test call with a visible transcript (testing) or a scored production call (observability).
The One Principle
Keep onboarding minimal, but it may only end at a verified working loop — never at "records created".
- Minimal: one high-leverage connection step per provider; everything else (SDK, mock tools, KB, dynamic variables, custom metrics) is deferred to after the first result.
- Verified: onboarding is NOT done when the agent/scenario rows exist. It is done when one test call completed and its transcript is visible (testing), or one call log is ingested and scored (observability). A misconfigured SIP endpoint or unsupported phone number must surface during onboarding, not days later.
Two Paths
Both paths share Phases 0 and 2 (path choice, agent connection) and diverge after that. The first objective is always connecting the agent — there is no separate account/project phase: working tools prove auth, and a missing project is handled inline (projects_list / projects_create) on the way into Phase 2.
- Testing (default) — generate evaluators, run them against the agent in simulation, review results.
- Observability — ingest production call logs, attach metrics, evaluate, review.
Execution Model — Read This First
This skill executes one phase at a time, in order. For each phase:
- Announce the step in plain words (e.g. "Let's connect your agent") — phase numbers are internal navigation, never user-facing.
- Read the phase file (
phaseN-*.mdin this skill directory). Do not rely on memory of its contents. - Complete every task in the file and satisfy its gate condition.
- Confirm the step in plain words and move on without waiting for the user (no "Phase N complete").
Ask questions ONLY to collect missing inputs or resolve genuine ambiguity (provider choice, credentials, phone number, self-hosted confirmation). Don't pause to re-confirm an action the flow already implies — the user invoked onboarding, which is a request to create the agent, enable metrics, generate evaluators, and start the first verification run. (Your client's own tool-permission prompts still apply as normal.) No "ready to continue?", no "shall I create it?", no "want me to proceed?" — just do the step and narrate it. The one exception: when a gate is blocked (e.g. the testing-path description gate) present the blocker and the options.
What ships with it
13 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.
- agents/openai.yaml 261 B
- phase0-path.md 2.2 KB
- phase2-agent.md 17 KB
- phase3-observability-ingest.md 4.3 KB
- phase3-testing-metrics.md 2.1 KB
- phase4-observability-metrics.md 1.7 KB
- phase4-testing-evaluators.md 2.8 KB
- phase5-observability-evaluate.md 1.0 KB
- phase5-testing-first-run.md 4.0 KB
- phase6-observability-review.md 1.0 KB
- phase6-testing-next.md 1.6 KB
- references/api-quickstart.md 2.8 KB
- references/client-setup.md 1.5 KB
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.
- 3d ago Changed · +2 lines · +35 tokens per session 81b7f54f438c
- 12d ago First seen · 79 lines · 121 tokens per session scan A 12b5384f636f
cekura-onboarding is a skill published in the GitHub repository cekura-ai/cekura-skills (7 stars, last pushed yesterday), licensed MIT. It adds 156 tokens to every session and 1,450 once invoked, about $0.0008 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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