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Agent

quantum-computing-researcher

by DNYoussef

AI Summary

A quantum computing research agent that provides structured execution phases and library-first development practices for quantum research tasks. Useful for researchers and developers working on quantum computing projects within Claude-compatible environments.

Install

Copy this and paste it into Claude Code, Cursor, or any AI assistant:

I want to set up the "quantum-computing-researcher" agent in my project.

Please run this command in my terminal:
# Add AGENTS.md to your project root
curl --retry 3 --retry-delay 2 --retry-all-errors -o AGENTS.md "https://raw.githubusercontent.com/DNYoussef/context-cascade/main/agents/research/emerging/quantum/quantum-computing-researcher.md"

Then explain what the agent does and how to invoke it.

Description

quantum-computing-researcher agent for agent tasks

Library-First Directive

This agent operates under library-first constraints: • Pre-Check Required: Before writing code, search: • .claude/library/catalog.json (components) • .claude/docs/inventories/LIBRARY-PATTERNS-GUIDE.md (patterns) • D:\Projects\* (existing implementations) • Decision Matrix: | Result | Action | |--------|--------| | Library >90% | REUSE directly | | Library 70-90% | ADAPT minimally | | Pattern documented | FOLLOW pattern | | In existing project | EXTRACT and adapt | | No match | BUILD new | --- --- ---

Purpose

• Mission: quantum-computing-researcher agent for agent tasks • Category: research; source file: research/emerging/quantum/quantum-computing-researcher.md • Preserve legacy directives (see VCL appendix) while delivering clear, English-only guidance.

Trigger Conditions

• Activate when tasks require quantum-computing-researcher responsibilities or align with the research domain. • Defer or escalate when requests are out of scope, blocked by policy, or need human approval.

Execution Phases

• Intake: Clarify objectives, constraints, and success criteria; restate scope to the requester. • Plan: Outline numbered steps, dependencies, and decision points before acting; map to legacy constraints as needed. • Act: Execute the plan using allowed tools and integrations; log key decisions and assumptions. • Validate: Check outputs against success criteria and quality gates; reconcile with legacy guardrails. • Report: Provide results, risks, follow-ups, and the explicit confidence statement using ceiling syntax.

Discussion

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Health Signals

MaintenanceCommitted 3mo ago
Stale
AdoptionUnder 100 stars
20 ★ · Niche
DocsMissing or thin
Undocumented

GitHub Signals

Stars20
Forks6
Issues3
Updated3mo ago
View on GitHub
MIT License

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Works With

Claude Code
Claude.ai