agentleFS
lschGSLlschGSL/claude_code_template/skills/ai-agents/agent-evaluation/SKILL.md

agent-evaluation

Skill1 starsChanged 7 months agoNo licenceView on GitHub

Testing and benchmarking LLM agents including behavioral testing,

21 other projects use a version of this, 4 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use tool-design, kubernetes and 5 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • mjunaidcaSkill

    tool-design

    Design tools that agents can use effectively. Use when creating new tools for agents, debugging tool-related failures, or optimizing existing tool sets.

    Also in 3 projects that use this

  • mjunaidcaSkill

    kubernetes

    Production-grade Kubernetes manifests and debugging for containerized applications. This skill should be used when users ask to deploy to Kubernetes, create K8s manifests, containerize for K8s, set up Deployments/Services/Jobs/StatefulSets/CronJobs, create namespaces with resource quotas, set up multi-team isolation, configure ResourceQuota/ LimitRange, secure with RBAC (ServiceAccount, Role, RoleBinding), configure init containers (model download, db wait, migrations), set up sidecars (logging, metrics), or debug pods (CrashLoopBackOff, logs, exec, describe, events). Auto-detects from Dockerfile/code, generates hardened manifests with educational comments. CKAD-aligned.

    Also in 3 projects that use this

  • MicrosoftSkill

    github-actions

    Use when creating, editing, reviewing, or troubleshooting GitHub Actions workflows in Scope.

    Also in 3 projects that use this

  • mrgoonieSkill

    context-engineering

    Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.

    Also in 4 projects that use this

  • wrsmith108Skill

    docker

    Container-based development for isolated, reproducible environments. Use when running npm commands, installing packages, executing code, or managing project dependencies. Trigger phrases include "npm install", "run the build", "start the server", "install package", or any code execution request.

    Also in 3 projects that use this

  • GoogleSkill

    code-review

    Adversarial systems, concurrency, memory-model, and architecture code review protocol. Use this skill whenever asked to review code, PRs, diffs, or branches in Filament.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 17 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 17 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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