langchain-architecture
Design LangChain LLM Architecture
LangChain applications can become hard to structure as agents, tools, memory, and retrieval grow. This skill gives Claude, Codex, and Claude Code practical architecture patterns for modular LLM workflows.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "langchain-architecture" from https://skillstore.io/skills/wshobson-langchain-architecture.md and its manifest at https://skillstore.io/api/skills/wshobson-langchain-architecture/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "langchain-architecture". Design a support assistant that can search policies and answer follow-up questions.
Expected outcome:
A recommended architecture with a conversational agent, policy retriever, windowed memory, callback logging, and tests for tool selection.
Using "langchain-architecture". Choose memory for a customer onboarding chat that may last many turns.
Expected outcome:
A comparison of buffer, summary, window, entity, and vector memory with a recommended hybrid approach.
Using "langchain-architecture". Review my LangChain pipeline before launch.
Expected outcome:
A production checklist covering validation, error handling, observability, token costs, streaming behavior, and fallback strategy.
Security Audit
SafeAll static external command findings are false positives caused by Markdown fenced Python examples. The network reconnaissance finding is also a false positive because the cited line describes general LangChain agent design, not scanning activity.
Risk Factors
⚙️ External commands (19)
Share & cite this report
Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.
Copy report link
https://skillstore.io/skills/wshobson-langchain-architecture/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
[](https://skillstore.io/skills/wshobson-langchain-architecture?utm_source=security_passport_badge)HTML badge
<a href="https://skillstore.io/skills/wshobson-langchain-architecture?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/wshobson-langchain-architecture/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/wshobson-langchain-architecture.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
wshobson. (2026). langchain-architecture security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/wshobson-langchain-architecture/audits/7BibTeX citation
@techreport{wshobson-wshobson-langchain-architecture-2026,
author = {wshobson},
title = {langchain-architecture security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/wshobson-langchain-architecture/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "langchain-architecture security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "wshobson"
date-released: "2026-07-07"
url: "https://skillstore.io/skills/wshobson-langchain-architecture/audits/7"
identifiers:
- type: other
value: "skillstore:wshobson-langchain-architecture:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
3 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
sickn33-langchain-architecture
2026-08-21
wshobson-langchain-architecture
2026-08-21
langchain-architecture
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Plan a LangChain Agent
Map agent type, tools, memory, and callback needs before implementation begins.
Design Retrieval Workflows
Structure document loading, chunking, vector storage, and source-aware retrieval flows.
Prepare Production Readiness
Review testing, observability, rate limits, error handling, and performance practices.
Try These Prompts
Use this skill to design a simple LangChain agent for my task. Include the agent type, required tools, memory choice, and failure handling.
Use this skill to design a LangChain RAG workflow for these documents and questions. Recommend loaders, splitters, vector storage, retrieval settings, and source handling.
Use this skill to compare LangChain memory options for my chat application. Explain tradeoffs for cost, context length, accuracy, and implementation complexity.
Use this skill to review my LangChain architecture for production. Check agents, tools, prompts, memory, callbacks, testing, rate limits, and observability.
Best Practices
- Define tool descriptions clearly so agents select the right action.
- Limit memory growth with summaries, windows, or retrieval-backed history.
- Add callbacks and tests before deploying agent workflows.
Avoid
- Giving agents broad tool access without validation or approval steps.
- Storing full conversation history without token or privacy limits.
- Shipping retrieval workflows without source checks or evaluation tests.