eval-and-trace-designer — for Claude Code eval-and-trace-designer, Discharge-Gatekeeper, community, for Claude Code, ide skills, AGENTS.md, PLAN.md, Clinical Intelligence MCP, Designer, adding

v2.0

Sobre este Skill

Cenario recomendado: Ideal for AI agents that need eval and trace designer. Resumo localizado: eval-and-trace-designer helps AI agents handle repository-specific developer workflows with documented implementation details.

Recursos

Eval and Trace Designer
Use this skill when
adding or revising eval prompts
defining failure and fallback assertions
checking parseability or citation rules

# Core Topics

Arshgill01 Arshgill01
[1]
[0]
Updated: 4/18/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
41
Canonical Locale
en
Detected Body Locale
en

Cenario recomendado: Ideal for AI agents that need eval and trace designer. Resumo localizado: eval-and-trace-designer helps AI agents handle repository-specific developer workflows with documented implementation details.

Por que usar essa habilidade

Recomendacao: eval-and-trace-designer helps agents eval and trace designer. eval-and-trace-designer helps AI agents handle repository-specific developer workflows with documented implementation details.

Melhor para

Cenario recomendado: Ideal for AI agents that need eval and trace designer.

Casos de Uso Práticos for eval-and-trace-designer

Caso de uso: Applying Eval and Trace Designer
Caso de uso: Applying Use this skill when
Caso de uso: Applying adding or revising eval prompts

! Segurança e Limitações

  • Limitacao: Requires repository-specific context from the skill documentation
  • Limitacao: Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is eval-and-trace-designer?

Cenario recomendado: Ideal for AI agents that need eval and trace designer. Resumo localizado: eval-and-trace-designer helps AI agents handle repository-specific developer workflows with documented implementation details.

How do I install eval-and-trace-designer?

Run the command: npx killer-skills add Arshgill01/Discharge-Gatekeeper/eval-and-trace-designer. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for eval-and-trace-designer?

Key use cases include: Caso de uso: Applying Eval and Trace Designer, Caso de uso: Applying Use this skill when, Caso de uso: Applying adding or revising eval prompts.

Which IDEs are compatible with eval-and-trace-designer?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for eval-and-trace-designer?

Limitacao: Requires repository-specific context from the skill documentation. Limitacao: Works best when the underlying tools and dependencies are already configured.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add Arshgill01/Discharge-Gatekeeper/eval-and-trace-designer. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use eval-and-trace-designer immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

eval-and-trace-designer

Install eval-and-trace-designer, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Eval and Trace Designer

Use this skill when

  • adding or revising eval prompts
  • defining failure and fallback assertions
  • checking parseability or citation rules
  • protecting hidden-risk and reconciliation behavior from drift

First read

  1. AGENTS.md
  2. PLAN.md
  3. docs/evals.md
  4. docs/phase0-hidden-risk-prompt-contract.md
  5. docs/phase0-orchestrator-decision-matrix.md

Goal

Keep the two-MCP plus external-A2A system inspectable and testable.

Required eval lenses

  1. Phase 1: Clinical Intelligence MCP smoke
  2. Phase 2: two-MCP integration
  3. Phase 3: external A2A orchestration
  4. parseability and citation gates
  5. failure and fallback behavior

Always check

  • output is valid JSON without repair
  • citations map to real inputs
  • duplicate hidden-risk findings are suppressed
  • contradictory evidence does not become confident prose
  • fallback direct-MCP behavior is documented when the A2A path fails

Do not

  • write evals that assume hidden state
  • reward verbosity over inspectability
  • ignore null-result behavior for hidden-risk review

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