What is create-evals?

A workflow for creating test cases for an AgentOS agent, where a test case describes a situation and the behavior that should be checked. It uses the agent's promises and past sessions to decide what the test suite should cover.

Use it to add cases to the evaluation suite, test a source or Studio-built agent, and identify important successes and failure modes.

It makes an agent's claimed behavior testable and reveals gaps that example tests may miss. It also runs and audits the cases so the resulting coverage is checked.

How agno-agi/agentos-modal configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to agno-agi/agentos-modal. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/agno-agi/agentos-modal/main/.agents/skills/create-evals/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/agno-agi/agentos-modal

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/agno-agi/agentos-modal/create-evals.svg)](https://agentmods.dev/skills/agno-agi/agentos-modal/create-evals)

Your own site

<a href="https://agentmods.dev/skills/agno-agi/agentos-modal/create-evals"><img src="https://agentmods.dev/badge/skills/agno-agi/agentos-modal/create-evals.svg" alt="Measured on agentmods" height="20"></a>

Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,300 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 100% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00089	$0.01300
Opus 5	$0.00044	$0.00650
Sonnet 5	$0.00018	$0.00260
Haiku 4.5	$0.00009	$0.00130

Measured 6d ago against content hash 026e02916d3e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

create-evals 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 6d 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.

Origin

This is a copy

100% identical to create-evals — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/create-evals/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Evals

Coding-agent workflow: run as /create-evals or by describing the task.

Turn what an agent promises into Case entries in evals/cases.py. The template's cases cover the reference components only; a user-built agent is invisible to the suite until this skill writes one. Failing suite → eval-and-improve; agent needs hardening → improve-agent.

Preconditions: Postgres on 5432, venv active (source .venv/bin/activate; ./scripts/venv_setup.sh if missing), .env populated.

Be self-driving: the repo and the database answer most questions. Ask the user only what they alone know — which jobs matter and which failures would hurt. One pick per exchange, recommendation first.

1. Pick the agent

The user's choice, or the least-covered component — almost always one of theirs. Source components have a file under agents/ or teams/. Studio-built components have none: Agent.load("<id>", db=eval_db, registry=registry, published_only=True) (or Team.load) rehydrates the published config at import time; it returns None for an archived or unpublished component, and a Case with neither field set raises — guard the load or the whole suite fails at import. Workflows cannot be case targets.

2. Map what it promises

Read the file (or the published config: eval_db.get_config(component_id="<id>")["config"]). Every "always", "never", "use X for Y" is a case. Note the tools for reliability assertions.

Two checks decide the hooks:

Can the run reach the ungated create/edit/publish Studio tools? StudioTools directly or through a team member — platform-builder always, and an agno case one delegation from a build. Those take **BUILDER_HOOKS.
Does it carry learning stores (learning=) or the shared_notes toolkit? Those take **LEARNING_HOOKS. Builder hooks are a strict superset; when in doubt, take them.

3. Mine the platform

from db import get_postgres_db
db = get_postgres_db()
sessions, _ = db.get_sessions(component_id="<agent-id>", limit=20, deserialize=False)
asks = [run["input"]["input_content"] for s in sessions for run in (s.get("runs") or []) if run.get("input")]
evals, _ = db.get_eval_runs(limit=20, deserialize=False)

Read the full file on GitHub · 79 lines

Changes

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.

6d ago First seen · 79 lines · 89 tokens per session scan A 026e02916d3e

Subscribe to this mod's changes

create-evals is a skill published in the GitHub repository agno-agi/agentos-modal (2 stars, last pushed 6d ago), licensed Apache-2.0. It adds 89 tokens to every session and 1,300 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to create-evals, differing in 0 lines, and is treated as a copy.

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