LLM & Agent Builder Copilot
ChatGPT pluginDesign reliable AI agents
Design, implement and review LLM applications and tool-using agent systems without adding unnecessary autonomy. Compare deterministic code, single model calls, bounded tools, directed workflows, autonomous agents and multi-agent systems. Define secure tool contracts, permissions, approval flows, MCP integration, state and memory, evaluations, tracing, debugging, migrations and production readiness. Includes focused specialist skills, reusable templates, technical references and offline fixtures. It is skills-only: coding, real subagents, tools, eval execution and deployment require user-authorized capabilities available in the host environment.
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Rank in Developer tools
5 listing changes logged · latest Nov 4: Capabilities, Description, Skills and 2 more. See what changed
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Developer tools443rd of 900 by placement
| # | Plugin | Position | 7d |
|---|---|---|---|
| 441 | #5221 | 58places down | |
| 442 | #5237 | 4,080places up | |
| 443 | #5239 | 78places up | |
| 444 | #5241 | 82places down | |
| 445 | #5244 | 227places up |
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12 more on the publisher’s page.
Example prompts
- “Choose the simplest reliable LLM or agent architecture for this use case.”
- “Design secure tools, approvals, state and recovery for this agent.”
- “Review this agent workflow for security, evaluation and reliability gaps.”
Skills
choose-system-complexity
Choose an appropriate autonomy and model complexity level for an LLM feature, rejecting gratuitous agents.
debug-agent-run
Diagnose incorrect tool calls, broken handoffs, unstable loops, model drift or production failures using traces and code.
design-agent-architecture
Design a bounded autonomous agent or directed agentic workflow, including tool loops, stopping conditions, context and recovery.
design-agent-evals
Design reproducible LLM and agent evaluations across quality, tool use, trajectories, state changes, risk, latency and cost.
design-guardrails-and-approvals
Specify human approval gates, deterministic guardrails, external-action boundaries, and safe recovery for agent systems.
design-llm-system
Architect an LLM application from requirements including model calls, structured outputs, data boundaries and failure cases.
design-mcp-integration
Plan MCP servers, clients, tools, resources, prompts, authorization and optional UI/task extensions without inventing protocol behavior.
design-tool-contracts
Design validated, least-privilege tool schemas, side-effect classifications, retries, idempotency and authorization.
get-started
Route requests about designing or improving LLM applications, agents, tools, MCP, evaluations or orchestration to the correct specialized workflow.
implement-agent-workflow
Implement or refactor LLM or agent workflows in an available repository with reliable tests and minimal unrelated changes.
manage-state-and-memory
Design safe session context, durable workflow state, user preferences, vector memory and external source-of-truth boundaries.
migrate-agent-framework
Plan or implement migrations of LLM APIs, agent SDKs or orchestration frameworks while preserving user-visible behavior.
Show all 18Show fewer
optimize-agent-reliability
Optimize tool-using agents for success, latency and cost with evidence rather than speculative model routing.
orchestrate-specialists
Choose and coordinate multi-agent designs only when independent specialists materially improve the result.
prepare-agent-release
Review agent systems before production rollout, including approvals, monitoring, evaluations, failure handling and rollback.
review-agent-eval-results
Inspect actual agent evaluation runs and distinguish measured regressions from anecdotal impressions.
review-agent-security
Threat-model agent and LLM integrations for prompt injection, exfiltration, confused-deputy actions, tenant leaks and secrets.
trace-and-observe
Plan trace instrumentation, debugging signals, privacy-safe logs and operational monitoring for tool-using LLM systems.
- Categories
- Made by
- Tekris Labs · Website
- Sign-in
- On Install
- Capabilities
- Select the lowest-complexity reliable LLM or agent architecture, Design bounded agent workflows, routes, handoffs and specialists, Define safe tool schemas, scopes, side effects and approvals, Design MCP integration and compatible client/tool boundaries, Plan session context, workflow state and durable memory, Create evaluation datasets, graders and regression criteria, Diagnose tool-loop failures, stale state and approval errors, Review prompt injection, tenant isolation and security risks, Design tracing, incident recovery and cost-aware optimization, Prepare versioned production rollout and rollback checklists
- Availability
- Available
- Version
- 0.2.0
- Keywords
- llm, agents, tool-calling, mcp, agent-systems, orchestration, evals, guardrails, observability
- Created
- September 23, 2026
- More info
- Sponsorship
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