Skip to content
Back to skills

Prompt Evaluation Runner

ASecurity

Use when evaluating prompts, LLM outputs, red-team suites, or model behavior with local eval configs and safe provider/cost controls.

  • 4 stars
  • 0 votes
  • 0 copies
  • 5 views
  • Added September 12, 2026
developmentjavascriptpythonjavaapi

Works with

  • api

Security analysis

A100/100

Pro scans all 2 files and shows the line behind each finding

Scanned September 12, 2026

npx -y skills add aibot88/sec_skill_store --skill prompt-evaluation-runner --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Prompt Evaluation Runner?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Prompt Evaluation Runner
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/aibot88-prompt-evaluation-runner/badge)](https://www.skillsdirectory.com/skills/aibot88-prompt-evaluation-runner)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: prompt-evaluation-runner
description: Use when evaluating prompts, LLM outputs, red-team suites, or model behavior with local eval configs and safe provider/cost controls.
---

# Prompt Evaluation Runner

## When to use
Use this skill when you need to evaluate an LLM app, test a prompt, or run red-teaming/vulnerability scans against a target model or application.

## Requirements / Checks
1. Check if an evaluation tool is defined in project deps, scripts, lockfiles, or local toolchain.
2. Do not run external commands like `npx Prompt evaluation@latest` directly.
3. If missing, ask before adding a local dev dependency or using an ephemeral runner.
4. Confirm expected cost, provider, API keys, and network target before execution.

## Workflow
1. **Define risk**: State target behavior, failure mode, provider(s), and budget limits.
2. **Choose assertions**: Prefer deterministic checks first: exact/contains/regex/JSON/schema/javascript/python/cost/latency.
3. **Use model graders sparingly**: Pin grader provider/model and explain cost/non-determinism.
4. **Configure minimally**: Keep config to description, env refs, prompts, providers, default assertions, and tests.
5. **Handle env safely**: Use templated env references such as `{{env.NAME}}`; never hardcode keys.
6. **Execute locally**: Run smallest suite first. Ask before long, paid, red-team, or production-targeted runs.
7. **Analyze failures**: Separate prompt failures, provider variance, flaky graders, bad fixtures, and config mistakes.

## Safety Constraints
- Do NOT log, echo, or store secrets (API keys) in configuration files or chat output.
- Do NOT run evaluations against production endpoints without user consent.
- Avoid executing arbitrary remote code or unvetted plugins during evaluation.

## Validation / Done Criteria
- Evaluation config is valid, minimal, and uses safe env refs.
- Deterministic assertions exist where possible.
- Run scope, provider, and cost are reported.
- Results are summarized without leaking sensitive data.

## References
- `references/eval-config-patterns.md`

Files in this skill

  • SKILL.md2 KB
  • source.json689 B

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.