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 tikalk/adlc-team-skills --skill evals-initgit clone --depth 1 https://github.com/tikalk/adlc-team-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/tikalk/adlc-team-skills/evals-init)<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.
<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>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00888 |
| Opus 5.5 | $0.00017 | $0.00355 |
| Sonnet 5.5 | $0.00008 | $0.00178 |
| Haiku 4.5 | $0.00004 | $0.00089 |
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 1mo 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 — 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:
- Directory Structure -
evals/{system}/with proper organization (promptfoo | deepeval) - Security Baseline - Auto-created graders for PII leakage, prompt injection, hallucination detection, misinformation detection
- Configuration Files - Standalone config.yml and goldset templates under
.adlc/evals/ - Auto-handoff to
/evals-specifyto 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-validateto run tests, or/evals-specifyto 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— Choosepromptfooordeepeval. 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
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.
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.
- 1mo ago Changed · +5 tokens per session eee681a5ee0d
- 1mo ago First seen · 83 lines · 37 tokens per session scan A 7d064c19a632
evals-init is a skill published in the GitHub repository tikalk/adlc-team-skills (143 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 888 once invoked, about $0.0002 per session on Opus 5.5. 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.
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