langchain-prompt-engineering
Best for LangChain 1.0 codebases wit…Works with GitHubLow risk
⌘source
- author
@jeremylongshore- language
- Python
★2kstars
268forks
Apr 22, 2026
✦overview.md
Key Features
- ·Version control for LangChain prompts via LangSmith prompt hub
- ·XML-tag conventions for Claude model prompts
- ·Few-shot example selection capabilities
- ·Discriminated-union extraction schemas
- ·A/B test wiring for prompt changes
- ·Migration from f-strings to ChatPromptTemplate
Use Cases
- →Managing 47 prompt strings embedded as f-string literals across 12 Python files
- →Migrating prompts from f-strings to ChatPromptTemplate
- →Optimizing prompts for different models (Claude, GPT-4o, Gemini)
- →A/B testing a prompt change without shipping code
- →Rolling back prompt versions without requiring full deploys
Best for
- ✓LangChain 1.0 codebases with embedded prompts
- ✓Teams managing multiple prompt versions
- ✓Production systems requiring prompt A/B testing
Not ideal for
- !One-off prompt experiments
- !Non-LangChain prompt management
name
langchain-prompt-engineering
description
Manage LangChain 1.0 prompts like code — LangSmith prompt hub versioning,
XML-tag conventions for Claude, few-shot example selection, discriminated-union
extraction schemas, and A/B test wiring. Use when taking ad-hoc prompts into
version control, migrating prompts from f-strings to ChatPromptTemplate,
optimizing prompts for Claude vs GPT-4o vs Gemini, or A/B testing a prompt
change. Trigger with "langchain prompt hub", "langsmith prompts",
"prompt versioning", "claude xml prompt", "few-shot example selector",
"prompt engineering".
license
MIT
allowed-tools:Read, Write, Edit, Bash(python:*), Bash(pip:*)
version:2.0.0
author:Jeremy Longshore <jeremy@intentsolutions.io>
tags:["saas","langchain","langgraph","python","langchain-1.0","prompts","langsmith","prompt-engineering"]
compatible-with:claude-code, codex
LangChain Prompt Engineering (Python)
Overview
A team inherits a LangChain 1.0 codebase with 47 prompt strings embedded as
f-string literals across 12 Python files. Nobody knows which version is live in
production. Rollback is git-only — requires a deploy. An A/B test on a single
prompt requires shipping code and running two services in parallel. A user pastes
a JSON snippet containing { into a chat endpoint and the whole thing throws:
KeyError: '"model"'
File ".../langchain_core/prompts/string.py", line ..., in format
That is pain-catalog entry P57 — ChatPromptTemplate.from_messages with
f-string templates treat every brace-delimited identifier as a variable
marker — including ones that appear inside user content. Any literal braces in
user input (code snippets, JSON, LaTeX, CSS selectors) crash the chain. Four
prompt-layer pitfalls this skill fixes:
- P57 — f-string template breaks on literal
{in user input - P58 — Claude expects system content in the top-level
systemfield, not a laterHumanMessage; reordering middleware silently loses persona - P53 — Pydantic v2 strict default rejects the helpful extra fields
$install
1-click copynpx skills add jeremylongshore/claude-code-plugins-plus-skills --skill langchain-prompt-engineeringSafety assessment
★
Clarity score
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1/ 5
poorThe SKILL.md content is hard to understand and quite ambiguous.
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1/ 5
not actionableThe SKILL.md is hard to act on; an agent would not know what to do.