langchain-context

langchain-context is a skill for Claude Code, Codex from nick-railsback/skill-engine. It costs 101 tokens per session (2,868 once invoked), scanned A, original, MIT.

A reference guide for answering questions about the LangChain Python ecosystem and its related projects, including LangGraph, LangSmith, Deep Agents, partner integrations, and the JavaScript repository.

In plain words
What is it for?
Use it to navigate LangChain architecture, packages, repositories, integrations, and documentation, and to locate the right reference for a specific ecosystem question.
Why use it?
It helps identify which LangChain package or companion project a question concerns. This reduces confusion between current, legacy, partner, and JavaScript components.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/nick-railsback/skill-engine/langchain-context
Any agent
npx skills add nick-railsback/skill-engine --skill langchain-context
Clone the repo
git clone --depth 1 https://github.com/nick-railsback/skill-engine

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for langchain-context

README.md
[![agentmods](https://agentmods.dev/badge/skills/nick-railsback/skill-engine/langchain-context.svg)](https://agentmods.dev/skills/nick-railsback/skill-engine/langchain-context)
Your own site
<a href="https://agentmods.dev/skills/nick-railsback/skill-engine/langchain-context"><img src="https://agentmods.dev/badge/skills/nick-railsback/skill-engine/langchain-context.svg" alt="Measured on agentmods" height="20"></a>
Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,868 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00101 $0.02868
Opus 5 $0.00051 $0.01434
Sonnet 5 $0.00020 $0.00574
Haiku 4.5 $0.00010 $0.00287

Measured 3d ago against content hash 4115d26b6622, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

langchain-context scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (verify.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

examples/langchain-context/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LangChain context navigator

Overview

This navigator covers the LangChain Python ecosystem in depth, plus a thin orientation pointer for the JS port:

  • Primary: the langchain-ai/langchain Python monorepo — langchain-core, the new langchain package (v1; built from libs/langchain_v1/), the legacy langchain-classic package (built from libs/langchain/), in-tree partner integrations, and the auxiliary libs (text-splitters, model-profiles, standard-tests).
  • Python companion repos: LangGraph (langchain-ai/langgraph), LangSmith SDK (langchain-ai/langsmith-sdk), Deep Agents (langchain-ai/deepagents), and the out-of-tree partner monorepos langchain-ai/langchain-google and langchain-ai/langchain-aws. Plus the docs source at langchain-ai/docs.
  • JS port (thin coverage only): langchain-ai/langchainjs is included as a pointer reference for orienting JS questions — full JS depth is out of scope; follow source links into the JS repo for non-trivial questions.

When asked a question this navigator's domain covers:

  1. Scan the Catalog below for the matching topic.
  2. Follow the link to read the reference file.
  3. If the question spans multiple references, consult the Cross-reference map.
  4. If a reference points at a source URL for deeper detail, follow it only if the reference itself didn't answer the question.

For first-time orientation — what packages exist, how langchain vs langchain-classic differ, where companion repos live — start with langchain-overview.md.

Claims policy

Cite by default, and make load-bearing claims verifiable:

  1. Inline-cite every load-bearing claim with its SHA-pinned permalink — the https://github.com/langchain-ai/langchain/blob/<sha>/libs/langchain_v1/langchain/agents/factory.py#L17-L25-style link the reference gives for that fact (versions, defaults, signatures, deprecations, behavior a user could get wrong by guessing). Put the permalink inline, on the claim. Use a bare filename parenthetical (e.g. (langchain-v1-agents.md)) only when the reference genuinely provides no permalink. This inline permalink is what the grounded-citation eval (SELF-AUDIT Check 8) grades.
  2. Don't cite orientational prose — "what is X?", "when did X launch?" — answer those from this navigator alone; opening a reference is itself a citation gesture.
  3. End with a one-line provenance footer, emitted italic, formatted *References consulted: foo.md, bar.md. Grounded in {{LIBRARY}}@{{VERSION}} — [reference index]({{INDEX_URL}}).* The footer is a summary of what you read — not a substitute for the inline permalinks on the claims. The {{LIBRARY}} / {{VERSION}} / {{INDEX_URL}} tokens are agent-substituted at answer time, so they appear literally in the stamped SKILL.md.
  4. If no reference was opened, say so in the footer ("Answered from general knowledge — no {{LIBRARY}} references consulted") — never fake it.

Read the full file on GitHub · 110 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 110 lines · 101 tokens per session scan A 4115d26b6622

Subscribe to this mod's changes

langchain-context is a skill published in the GitHub repository nick-railsback/skill-engine (2 stars, last pushed 27d ago), licensed MIT. It adds 101 tokens to every session and 2,868 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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