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Agent skill

Langchain Common Errors

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree.

MITAuto-check passedAI & LLM Engineering

Install Langchain Common Errors

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill langchain-common-errors -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace langchain-common-errors --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/langchain-common-errors .claude/skills/langchain-common-errors && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
langchain-common-errors
GitHub stars
2.8k
Token cost
~3.7k tokens
SKILL.md length
1,352 words
Files
6 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree.

  • Works in 5 steps: Triage first. Read the first line of the… → Match the message string, not the call… → Apply the named fix. If the entry points… → …
  • You have a traceback and want the specific fix
  • SKILL.md covers Overview, Prerequisites, Instructions and Catalog, plus 4 more sections
  • Calls pip and python

What it does

Langchain Common Errors is an agent skill from jeremylongshore/tons-of-skills-marketplace. Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree. Use when you have a traceback and want the specific fix, not speculative documentation. Covers ImportError (0.2/0.3 → 1.0 migration), AttributeError on AIMessage.content, KeyError in LCEL and prompts, GraphRecursionError, silent threadid memory loss, JSON-serialization crashes, and graphs that halt without reaching END. Trigger with "langchain error", "langgraph traceback"…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/errors/content-shape.md`, `references/errors/graph-traps.md` and `references/errors/import-migration.md`). Compatibility notes: Designed for Claude Code

It sits in AI & LLM Engineering, covering Building AI agents. It works with LangChain and LangGraph. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • You have a traceback and want the specific fix
  • Not speculative documentation
  • With langchain error
  • Langgraph traceback

Example prompts

  • “langchain error”
  • “langgraph traceback”
  • “OutputParserException”
  • “/langchain-common-errors”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Grep

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Triage first. Read the first line of the traceback. Look up the exception
  2. Match the message string, not the call site. Each catalog entry opens with
  3. Apply the named fix. If the entry points to a reference file, read that
  4. Verify with a test. Every catalog entry names a test that will catch the
  5. If no match: check docs/pain-catalog.md for the exception class name or

What it can do on your machine

Read from SKILL.md and the folder at commit 80f86df. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip
    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • python.langchain.com
    • blog.langchain.com
    • langchain-ai.github.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Langchain Common Errors loads about 3.7k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 162 tokens; SKILL.md has 1,352 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~162
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit 80f86df, republished under its MIT licence (© jeremylongshore). 1,352 words, ~3,684 tokens.

Download SKILL.mdSave it as .claude/skills/langchain-common-errors/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
langchain-common-errors
description
Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree. Use when you have a traceback and want the specific fix, not speculative documentation. Covers ImportError (0.2/0.3 → 1.0 migration), AttributeError on AIMessage.content, KeyError in LCEL and prompts, GraphRecursionError, silent thread_id memory loss, JSON-serialization crashes, and graphs that halt without reaching END. Trigger with "langchain error", "langgraph traceback", "OutputParserException", "GraphRecursionError", "ImportError langchain", "AttributeError AIMessage content".
allowed-tools
Read, Grep
compatibility
Designed for Claude Code
version
2.7.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, langchain, langgraph, python, langchain-1.0, errors, troubleshooting, debugging

LangChain Common Errors (Python)

Overview

The same twelve-plus LangChain 1.0 / LangGraph 1.0 tracebacks show up every week in production: ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models', AttributeError: 'list' object has no attribute 'lower', GraphRecursionError: Recursion limit of 25 reached, TypeError: Object of type datetime is not JSON serializable, KeyError: 'question' deep in LCEL internals. Stack traces are ambiguous, docs sprawl across 0.2 / 0.3 / 1.0 eras, and engineers lose 30–90 minutes per incident re-deriving the fix.

This skill is a paste-match catalog of 14 entries (E01–E14) grouped into 3 reference files by category, plus a triage decision tree. Every entry opens with the exact exception class and message string you see in your terminal, names the cause in one sentence with a pain-catalog code, and gives a one-line fix or a reference-file pointer. Pinned to langchain-core 1.0.x, langchain 1.0.x, langgraph 1.0.x, verified 2026-04-21.

Pain-catalog anchors: P02, P06, P09, P10, P16, P17, P38, P39, P40, P41, P42, P55, P56, P57, P66.

Prerequisites

  • Python 3.10+
  • A traceback or a reproducible bug — this skill is diagnostic, not preventive
  • langchain-core >= 1.0, < 2.0, langgraph >= 1.0, < 2.0, and any provider integration packages pinned to 1.0.x
  • anthropic >= 0.42 when using langchain-anthropic 1.0 (see E06)

Instructions

  1. Triage first. Read the first line of the traceback. Look up the exception class in the catalog below or in Triage Decision Tree.
  2. Match the message string, not the call site. Each catalog entry opens with the literal message pattern you see.
  3. Apply the named fix. If the entry points to a reference file, read that file for the deep walk-through including codemods, before/after code, and adjacent traps. Otherwise use the one-line fix here.
  4. Verify with a test. Every catalog entry names a test that will catch the error in CI next time.
  5. If no match: check docs/pain-catalog.md for the exception class name or a message substring. Do not add speculative fixes here without catalog evidence.

Catalog

Each entry is indexed as E## — ClassName: "message pattern" with a one-line cause (pain-catalog code) and a one-line fix or reference pointer.

Category A — Import & migration errors (0.2 / 0.3 → 1.0)

Full detail, before/after code, codemod commands: import-migration.md.

E01 — ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models'
  • Cause: Top-level langchain.chat_models / langchain.llms re-exports removed in 1.0 (P38).
  • Fix: from langchain_openai import ChatOpenAI. Run python -m langchain_cli migrate for automated rewrites. See E01 in import-migration.md.
E02 — AttributeError: module 'langchain' has no attribute 'LLMChain'
  • Cause: Legacy chain classes (LLMChain, SequentialChain, TransformChain) removed in 1.0 in favor of LCEL (P39).
  • Fix: chain = prompt | llm | StrOutputParser(); .run(x) becomes .invoke({"input": x}). See E02 in import-migration.md.
E03 — ImportError: cannot import name 'ConversationBufferMemory'
  • Cause: All legacy memory classes removed in 1.0; LangGraph checkpointing is the replacement (P40).
  • Fix: Use InMemorySaver / PostgresSaver + thread_id via LangGraph create_react_agent. See E03 in import-migration.md.
E04 — ImportError: cannot import name 'initialize_agent'
  • Cause: Legacy agent factories (initialize_agent, AgentType, create_openai_functions_agent) removed in 1.0 (P41).
  • Fix: from langgraph.prebuilt import create_react_agent; create_react_agent(model=llm, tools=tools, checkpointer=InMemorySaver()). See E04 in import-migration.md.
E05 — AttributeError: 'AgentAction' object has no attribute 'tool_name' (or inverse)
  • Cause: Legacy AgentAction / AgentFinish shape replaced by ToolCall objects; fields renamed .tool → .tool_name, .tool_input → .args (P42).
  • Fix: Access tool_call["name"] / tool_call["args"] on message .tool_calls, not result["intermediate_steps"]. See E05 in import-migration.md.
E06 — KeyError: 'input' inside tool_use block parsing
  • Cause: langchain-anthropic >= 1.0 requires anthropic >= 0.40; SDK tool-use schema changed (P66).
  • Fix: pip install "langchain-anthropic>=1.0,<2.0" "anthropic>=0.42,<1.0" in the same commit. See E06 in import-migration.md.
Category B — Content-shape & prompt-template errors

Full detail, block-iterator extractor, jinja2 escape pattern: content-shape.md.

E07 — AttributeError: 'list' object has no attribute 'lower' (or .strip, .split, .format)
  • Cause: AIMessage.content is list[dict] on Claude with any non-text block and on OpenAI once tools are bound (P02).
  • Fix: Use msg.text() (LangChain 1.0+) or iterate and filter block["type"] == "text". See E07 in content-shape.md.
E08 — KeyError: '<var>' inside runnables/passthrough.py or runnables/base.py
  • Cause: LCEL dict-shape mismatch between runnable stages; error surfaces at the consumer, not the producer (P06).
  • Fix: Insert RunnableLambda debug probes between stages and enable set_debug(True). See E08 in content-shape.md.
E09 — KeyError: '<var>' inside prompts/chat.py or prompts/prompt.py on user input
  • Cause: ChatPromptTemplate.from_messages defaults to f-string parsing; user-provided { / } characters are parsed as template variables (P57).
  • Fix: Use MessagesPlaceholder("history") for variable content, or template_format="jinja2" for free-text templates, or escape literals as {{ / }}. See E09 in content-shape.md.
Category C — Agent & graph execution traps

Full detail, diagnostic callbacks, thread_id middleware, router asserts: graph-traps.md.

E10 — GraphRecursionError: Recursion limit of 25 reached without hitting a stop condition
  • Cause: create_react_agent and StateGraph.compile() default recursion_limit=25 counts supersteps, not loop iterations; vague prompts never converge (P10, P55).
  • Fix: Set recursion_limit=10 for interactive use; add terminal edge on repeated tool-call names. See E10 in graph-traps.md.
E11 — AgentExecutor returns "I couldn't find the answer" on every tool call, no exception
  • Cause: handle_parsing_errors=True catches tool exceptions and passes str(exc) (often empty) as observation; loop continues without signal (P09).
  • Fix: return_intermediate_steps=True, handle_parsing_errors=False or migrate to LangGraph create_react_agent. See E11 in graph-traps.md.
Show full SKILL.md (553 more words)Show less
E12 — Multi-turn chat forgets everything between calls, no exception
  • Cause: LangGraph checkpointers key state by config["configurable"]["thread_id"]; omitted thread_id means every invocation gets a fresh state with no warning (P16).
  • Fix: Require thread_id at app boundary; wrap in middleware that raises on missing key. See E12 in graph-traps.md.
E13 — TypeError: Object of type <datetime / bytes / Decimal / set> is not JSON serializable
  • Cause: InMemorySaver / PostgresSaver / SqliteSaver serialize state as JSON on every superstep; non-primitives break at interrupt or checkpoint boundary (P17).
  • Fix: Keep state JSON-primitive only (str/int/float/bool/list/dict); serialize at node boundaries; or use JsonPlusSerializer for Pydantic v2. See E13 in graph-traps.md.
E14 — Graph halts without reaching END, no exception, no log
  • Cause: add_conditional_edges(node, router, path_map) where router returns a string not in path_map causes silent termination on some 1.0 versions (P56).
  • Fix: assert router_return in path_map; always include END explicitly; inspect graph.get_state(cfg).next. See E14 in graph-traps.md.

Output

  • Named cause tied to a P## pain-catalog code for every traceback
  • Named fix (one-line or a reference-file walk-through) tied to E## catalog entry
  • A regression test pattern that catches the error in CI next time
  • Triage path recorded for the incident retro (which entry matched, how long it took)

Error Handling

This skill is the error-handling reference for the pack. The triage workflow:

  1. First line of traceback → pick category in the table below.
  2. Exception class + message substring → pick E## entry above.
  3. Reference file → read the deep walk-through for before/after code and tests.
First-line patternCategoryEntriesReference
ImportError from langchain.*AE01, E03, E04import-migration.md
AttributeError on langchain.* moduleAE02import-migration.md
AttributeError on AgentAction / ToolCallAE05import-migration.md
ImportError / KeyError against langchain-anthropicAE06import-migration.md
AttributeError on list.lower / .stripBE07content-shape.md
KeyError in runnables/BE08content-shape.md
KeyError in prompts/BE09content-shape.md
GraphRecursionErrorCE10graph-traps.md
Silent wrong answers / empty tool errorsCE11graph-traps.md
Multi-turn memory loss, no exceptionCE12graph-traps.md
TypeError ... not JSON serializableCE13graph-traps.md
Graph halts without reaching ENDCE14graph-traps.md

For tracebacks that do not match: consult triage-decision-tree.md for the full routing flowchart, then docs/pain-catalog.md for any remaining pain codes. Escalate to the main thread before adding speculative fixes.

Examples

Example 1 — ImportError on a 0.3 → 1.0 upgrade

Incoming traceback:

Traceback (most recent call last):
  File "app.py", line 3, in <module>
    from langchain.chat_models import ChatOpenAI
ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models'

Triage:

  1. First line is ImportError from langchain.chat_models → Category A.
  2. Matches E01 exactly.
  3. Cause: top-level re-exports removed in 1.0 (P38).
  4. Fix: rewrite imports and bump provider packages.
bash
pip install "langchain-openai>=1.0,<2.0" "langchain-anthropic>=1.0,<2.0" "langchain-cli>=0.1"
python -m langchain_cli migrate src/
python
# Before
from langchain.chat_models import ChatOpenAI

# After
from langchain_openai import ChatOpenAI

Re-run tests. Next failure is almost always E07 (AIMessage.content shape) once the imports resolve — walk that one next from content-shape.md.

Example 2 — GraphRecursionError triage

Incoming traceback:

Traceback (most recent call last):
  File "worker.py", line 88, in run
    result = agent.invoke({"messages": [("user", q)]}, config=cfg)
  ...
langgraph.errors.GraphRecursionError: Recursion limit of 25 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.

Triage:

  1. Exception class is GraphRecursionError → Category C.
  2. Matches E10 exactly.
  3. Cause: vague prompt or tool loop; default recursion_limit=25 (P10, P55).
  4. Before raising the limit, diagnose first — attach a StepLogger callback (see graph-traps.md § E10) and count real steps. If the same two node names alternate, it is a convergence bug, not a budget bug.

Fix (budget only):

python
cfg = {"configurable": {"thread_id": tid}, "recursion_limit": 10}
agent.invoke(inp, config=cfg)

Fix (convergence + budget):

python
def _should_stop(state):
    recent = [m for m in state["messages"][-6:] if getattr(m, "tool_calls", None)]
    if len(recent) >= 3 and all(
        r.tool_calls[0]["name"] == recent[0].tool_calls[0]["name"] for r in recent
    ):
        return "end"
    return "continue"

graph.add_conditional_edges("agent", _should_stop, {"continue": "agent", "end": END})

Pair with a per-session token-budget middleware from langchain-cost-tuning.

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/.curated/langchain-common-errors of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/errors/content-shape.md
  • references/errors/graph-traps.md
  • references/errors/import-migration.md
  • references/errors/triage-decision-tree.md
  • references/one-pager.md

Open the folder on GitHubat commit 80f86df

Compare with similar skills

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Works with

Categories

Questions about Langchain Common Errors

What does Langchain Common Errors do?

Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree. Langchain Common Errors is an agent skill from jeremylongshore/tons-of-skills-marketplace.0 exceptions with named causes and named fixes, plus a triage decision tree.

When should I use Langchain Common Errors?

Langchain Common Errors fits situations like: you have a traceback and want the specific fix; not speculative documentation; with langchain error; langgraph traceback.

How do I install Langchain Common Errors in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langchain-common-errors -a claude-code`. Or copy the skill folder (skills/.curated/langchain-common-errors in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/langchain-common-errors in your project. Claude Code loads it when a task matches its description.

How do I install Langchain Common Errors in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langchain-common-errors -a codex`. Or copy the skill folder (skills/.curated/langchain-common-errors in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/langchain-common-errors in your project. Codex loads it when a task matches its description.

Can I use Langchain Common Errors in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langchain-common-errors -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langchain-common-errors, .gemini/skills/langchain-common-errors, .github/skills/langchain-common-errors and .opencode/skills/langchain-common-errors in your project.

What does Langchain Common Errors need to run?

Going by SKILL.md and its folder, Langchain Common Errors needs the command-line tools its instructions call (pip and python). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Langchain Common Errors access the network?

SKILL.md names 3 domains. As links in the text: python.langchain.com, blog.langchain.com and langchain-ai.github.io. This is read from the text; nothing was executed.

Is Langchain Common Errors safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Langchain Common Errors use?

Langchain Common Errors is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Langchain Common Errors use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.6k tokens, read only when the agent opens those files.

What are the alternatives to Langchain Common Errors?

Skills that share tags, products or a category with Langchain Common Errors: Mem0 Platform SDK (mem0ai/mem0, 67k stars), LangSmith Trace Debugging (ComposioHQ/awesome-claude-skills, 77k stars), Add Example Agent (GetBindu/Bindu, 10k stars) and Failproof AI SDK Integration (FailproofAI/failproofai, 5.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Langchain Common Errors?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,825 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 9, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.