llm-evals SKILL.md skillA
llm-evals from vodailocz/kilo-kit-mcp is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add vodailocz/kilo-kit-mcp/llm-evals@git:20260821.05c0d52Pins git:20260821.05c0d52 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- vodailocz/kilo-kit-mcp
- Path
skills/engineering/llm-evals/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260821.05c0d52, committed Aug 21, 2026
- Size
- 4,058 bytes
- Repository stars
- 27
- License
- Apache-2.0
Use when validating, benchmarking, or monitoring LLM application performance. Keywords: RAG evaluation, LLM-as-a-judge, CI/CD gating, trajectory scoring, test suites, prompt quality.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# LLM Evaluation & Validation Framework
## Overview
The `llm-evals` skill provides a systematic framework for evaluating and monitoring Large Language Model (LLM) applications throughout the development lifecycle. It bridges the gap between ad-hoc testing and production-grade reliability by implementing rigorous evaluation pipelines, metric-driven gating, and dataset versioning.
## When To Use
* Setting up automated evaluation pipelines for LLM chains.
* Developing or refining RAG (Retrieval-Augmented Generation) systems.
* Preparing LLM applications for production deployment.
* Investigating performance regressions in complex, multi-step agent trajectories.
* Defining custom rubrics for LLM-as-a-Judge scenarios.
## Core Concepts
* **Trajectory-Level Evaluation**: Scoring intermediate reasoning steps, tool choices, and argument precision, moving beyond just final output metrics.
* **LLM-as-a-Judge**: Using capable models (e.g., GPT-4o, Claude 3.5 Sonnet) as automated judges to score outputs based on user-defined rubrics.
* **Metric Tiers**:
* **Unit**: Single prompt/completion pairs.
* **Integration**: Individual chains or multi-step logic.
…Read the whole file at its exact version.
How to install
mdr add vodailocz/kilo-kit-mcp/llm-evals@sha256:1c1e3957a0db0890The line at the top of this page pins the label git:20260821.05c0d52, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_oj53md6ixpszp4z4)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Aug 21, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4058 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
vodailocz/kilo-kit-mcp · 27 stars · license Apache-2.0 · pushed 2026-10-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_oj53md6ixpszp4z4 GET https://markdownregistry.com/api/v1/resolve?ref=vodailocz/kilo-kit-mcp/llm-evals GET https://markdownregistry.com/api/v1/blob/1c1e3957a0db089092d7cb3c3f7d6883584e2a6a65929e89eb6e90788b9eeb5e
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.