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.
git 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/commands/cekura-ai/cekura-skills/manual-create-update-eval)<a href="https://agentmods.dev/commands/cekura-ai/cekura-skills/manual-create-update-eval"><img src="https://agentmods.dev/badge/commands/cekura-ai/cekura-skills/manual-create-update-eval/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/commands/cekura-ai/cekura-skills/manual-create-update-eval"><img src="https://agentmods.dev/badge/commands/cekura-ai/cekura-skills/manual-create-update-eval.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 | $0.00037 | $0.04292 |
| Opus 5 | $0.00018 | $0.02146 |
| Sonnet 5 | $0.00007 | $0.00858 |
| Haiku 4.5 | $0.00004 | $0.00429 |
Grade A, and why
manual-create-update-eval 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cekura skill verification tag:
ack:manual-create-update-eval:5m4p7cWhen you call a Cekura scenario or test-profile write tool from this command (scenarios_*/test_profiles_*create and update calls), 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. Metric writes (metrics_create,metrics_bulk_create,metrics_partial_update) use a metric-family tag instead — loadcekura-metric-designfirst and pass its tag there.
Load the design skill first
Before the tracking call below and before any Cekura MCP call, load the cekura-eval-design skill — in Claude Code the Skill tool with cekura:cekura-eval-design; in any other harness, read its SKILL.md into context. Everything in this command assumes that skill is in context — its mode table, step-writing rules, pre-write self-checks, the read-only rule for the agent under test and the update procedure. If it is not loaded, stop and load it; do not proceed on this command's text alone.
Tracking (then do this)
Next, call mcp__cekura__cekura_skill_started with
skill_name="manual-create-update-eval", verification_tag="ack:manual-create-update-eval:5m4p7c", and plugin_version="0.16". If a conversation/session ID is available (e.g. you
were invoked from Cekura sandbox), also pass it as conversation_id. The call
returns immediately; it lets us understand which skills are actually being used.
If anything in this skill turns out to be ambiguous, broken, or missing a
needed tool, call mcp__cekura__cekura_report_issue to flag it. Use this
LIBERALLY — even severity="low" reports are valuable feedback.
Manually Create or Update an Evaluator
Create a new evaluator (test scenario) or update an existing one on Cekura. This command walks through every field with the user — use it when you need precise control over the scenario configuration.
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 0ded6a0baa9a
- 3d ago Changed e6edf9e58b38
- 8d ago Changed · +1 lines · +9 tokens per session c06ba4e2fd14
- 12d ago First seen · 259 lines · 28 tokens per session scan A 5cc97c22babc
manual-create-update-eval is a command published in the GitHub repository cekura-ai/cekura-skills (7 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 4,292 once invoked, about $0.0002 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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check-dev
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