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LLM & Agent Builder Copilot

ChatGPT plugin

Design reliable AI agents

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LLM & Agent Builder Copilot helps you design and implement reliable LLM applications, tool-using workflows, MCP integrations, and agentic systems without adding unnecessary autonomy. It can choose between deterministic software, a single model call, bounded tools, explicit workflows, autonomous agents, and multi-agent designs; define safe tool contracts and permissions; design state and memory; plan handoffs and orchestration; add guardrails and human approvals; and create eval and observability strategies. It favors structured outputs, least privilege, bounded execution, recoverable state, and simple architectures.

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Movement

From our daily snapshots over the last 30 days.

Rank by placement

#5269of 8,79346places down24h103places down7d
#5,058#5,295#5,532#5,769Sep 27Oct 3Oct 9Oct 15Oct 21Oct 26

Rank in Developer tools

#468of 74210places down24h27places down7d
#421#449#477#505Sep 27Oct 3Oct 9Oct 15Oct 21Oct 26

In its category

How this plugin compares with others in the same category. Positions are counted within the category, not across the whole directory.

Developer tools468th of 742 by placement
#PluginPosition7d
466CompText Evidence#526322places up
467GodPrompt#5268116places down
468LLM & Agent Builder CopilotThis page#5269103places down
469Macroscope#527023places up
470Servotab#527115places up

All 742 Developer tools plugins

Example prompts

  • “Design the simplest reliable LLM or agent architecture for this use case.”
  • “Design safe tools, permissions, state, and approvals for this agent.”
  • “Review this agent workflow for unnecessary complexity, security risks, and eval gaps.”

Skills

  • llm-agent-builder

    Design and review LLM applications, tool-using workflows, MCP integrations, agentic systems, state, memory, guardrails, approvals, orchestration, tracing, and evaluations while choosing the lowest complexity that reliably satisfies the use case.

Categories
Made by
Krishna Sathvik
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On Install
Capabilities
Choose the simplest architecture from deterministic code through multi-agent systems, Design LLM applications, tool-using workflows, autonomous agents, and multi-agent systems, Define safe tool schemas, permissions, retries, idempotency, errors, and approval requirements, Design manager, handoff, router, parallel-worker, evaluator, and orchestrator patterns, Plan MCP tools, resources, prompts, authentication, long-running tasks, and observability, Design conversation state, workflow state, durable preferences, and application memory, Add guardrails, human approvals, least-privilege controls, and prompt-injection defenses, Create agent evaluations for task success, tool use, trajectories, side effects, latency, and cost, Design tracing and observability for model calls, tools, handoffs, approvals, retries, and outcomes, Use current official docs for model APIs, Agents SDK, MCP, tools, guardrails, and platform behavior
Availability
Available
Version
0.1.0
Keywords
llm, agents, mcp, tools, guardrails, evals, orchestration
Created
September 23, 2026
Sponsorship
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