evals-init

evals-init is a skill for Claude Code from tikalk/adlc-team-skills. It costs 37 tokens per session (883 once invoked), scanned A, original, MIT.

A setup command for an evaluation system: a structured way to test an AI application against expected results. It creates folders, configuration, starter datasets, and checks for issues such as personal-data leakage, prompt injection, made-up answers, and misinformation.

In plain words
What is it for?
Use it when starting systematic evaluation, adopting evaluation-driven development, or preparing PromptFoo or DeepEval tests for an AI application.
Why use it?
It gives a project an organized starting point for repeatable AI testing instead of relying only on ad hoc manual checks. It also prepares separate fast and more detailed evaluation levels.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it when starting systematic evaluation, adopting evaluation-driven development, or preparing PromptFoo or DeepEval tests for an AI application.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikalk/adlc-team-skills/evals-init
Install

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.

Any agent
npx skills add tikalk/adlc-team-skills --skill evals-init
Clone the repo
git clone --depth 1 https://github.com/tikalk/adlc-team-skills

Made for: Claude Code.

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.

agentmods badge for evals-init

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/evals-init/github.svg)](https://agentmods.dev/skills/tikalk/adlc-team-skills/evals-init)
Your own site
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/evals-init"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/evals-init/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.

agentmods 80×15 button for evals-init

Your own site · 80×15
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/evals-init"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/evals-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 883 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.00883
Opus 5 $0.00018 $0.00441
Sonnet 5 $0.00007 $0.00177
Haiku 4.5 $0.00004 $0.00088

Measured 9d ago against content hash 7d064c19a632, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

evals-init 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 9d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/bash/setup-evals-init.sh, scripts/powershell/setup-evals-init.ps1), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/evals/evals-init/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

evals-init

What this skill does

Initialize the project-level evaluation directory structure following EDD (Eval-Driven Development) principles to prepare for systematic evaluation development. This is completely standalone with zero spec-kit dependencies.

Output:

  1. Directory Structure - evals/{system}/ with proper organization (promptfoo | deepeval)
  2. Security Baseline - Auto-created graders for PII leakage, prompt injection, hallucination detection, misinformation detection
  3. Configuration Files - Standalone config.yml and goldset templates under .adlc/evals/
  4. Auto-handoff to /evals-specify to begin error analysis

Key EDD Principles Applied:

  • Principle I: Spec-Driven Contracts - Evals validate spec compliance
  • Principle II: Binary Pass/Fail - No Likert scales in grader templates
  • Principle IV: Evaluation Pyramid - Tier 1 (fast) + Tier 2 (goldset) structure
  • Principle IX: Test Data as Code - Version control setup for datasets

When to use

  • Starting systematic evaluation: Set up the initial evaluation harness for your application
  • EDD Adoption: Converting from traditional testing to evaluation-driven development
  • Security-first evaluation: Auto-generate baseline security checks from the start

When NOT to use

  • Evals directory already exists: Use /evals-validate to run tests, or /evals-specify to add criteria
  • Evaluating team directives: This is for project-level application behavior testing, not directives compliance

Process

User Input

$ARGUMENTS

Parse flags from the arguments first, then treat remaining text as focus areas:

  • --system SYSTEM — Choose promptfoo or deepeval. If omitted, choose interactively based on tech stack.
  • Remaining text — System description (focus setup)

Execution Steps

Phase 1: Tech Stack Detection
  • Scan project manifests (package.json, requirements.txt, Cargo.toml, go.mod, etc.)
  • Recommends PromptFoo for mixed/JS stacks; DeepEval for Python-native stacks

Read the full file on GitHub · 83 lines

Files

What ships with it

2 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.

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.

  1. 9d ago First seen · 83 lines · 37 tokens per session scan A 7d064c19a632

Subscribe to this mod's changes

evals-init is a skill published in the GitHub repository tikalk/adlc-team-skills (133 stars, last pushed 2d ago), licensed MIT. It adds 37 tokens to every session and 883 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 2026-08-30.