Agent Prompt Engineering
agentailor/fullstack-langgraph-nextjs-agent
Comprehensive guide for designing, refining, and auditing system prompts for autonomous AI agents based on Anthropic's production practices.
Reviews changes in the langchain-azure monorepo using package-specific knowledge of langchain-azure-ai, langchain-azure-compute, langchain-azure-cosmosdb, langchain-azure-postgresql…
$ npx skills add langchain-ai/langchain-azure --skill code-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install langchain-ai/langchain-azure code-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/langchain-ai/langchain-azure.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/code-review .claude/skills/code-review && rm -rf skills-srcUse ~/.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/
Install the "code-review" agent skill from https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-review into .claude/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add langchain-ai/langchain-azure --skill code-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install langchain-ai/langchain-azure code-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-azure.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/code-review .agents/skills/code-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "code-review" agent skill from https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-review into .agents/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add langchain-ai/langchain-azure --skill code-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install langchain-ai/langchain-azure code-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-azure.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/code-review .cursor/skills/code-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "code-review" agent skill from https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-review into .cursor/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/langchain-ai/langchain-azure.git --path .github/skills/code-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add langchain-ai/langchain-azure --skill code-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install langchain-ai/langchain-azure code-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-azure.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/code-review .gemini/skills/code-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-review into .gemini/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install langchain-ai/langchain-azure code-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add langchain-ai/langchain-azure --skill code-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-azure.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/code-review .github/skills/code-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-review into .github/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add langchain-ai/langchain-azure --skill code-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install langchain-ai/langchain-azure code-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-azure.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/code-review .opencode/skills/code-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/langchain-ai/langchain-azure/tree/main/.github/skills/code-review into .opencode/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
code-reviewReviews changes in the langchain-azure monorepo using package-specific knowledge of langchain-azure-ai, langchain-azure-compute, langchain-azure-cosmosdb, langchain-azure-postgresql…
Code Review is an agent skill from langchain-ai/langchain-azure, published by the product's own GitHub organization. Reviews changes in the langchain-azure monorepo using package-specific knowledge of langchain-azure-ai, langchain-azure-compute, langchain-azure-cosmosdb, langchain-azure-postgresql, langchain-azure-storage, langchain-sqlserver, and langchain-azure-dynamic-sessions, together with the LangChain, LangGraph, Deep Agents, and Azure SDK contracts each package must satisfy. Use this skill whenever reviewing a pull request or diff, checking code for bugs or regressions, or assessing changes under libs/, samples/, or…
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `references/azure-ai.md`, `references/azure-compute.md` and `references/azure-cosmosdb.md`).
It sits in AI & LLM Engineering, covering Building AI agents. It works with Microsoft Azure, LangChain, LangGraph and Azure Cosmos DB. The repository describes itself as: Build secure LangChain applications on Azure. The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 5784474. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
uvFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Code Review loads about 2.3k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 175 tokens; SKILL.md has 1,106 words of instructions outside code blocks.
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.
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.
The full file from langchain-ai/langchain-azure at commit 5784474, republished under its MIT licence (© langchain-ai). 1,106 words, ~2,304 tokens.
.claude/skills/code-review/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.Every directory under libs/ is a separately versioned, separately released
package with its own maintainers, dependency manager, conventions, and upstream
contracts. A finding is only useful if it is correct for the package it lands
in, so the first job in any review is to work out which package changed and
load that package's rules before judging anything.
Report defects the change introduces: incorrect behavior, broken edge cases, regressions in released public API, violations of an upstream contract (LangChain, LangGraph, Deep Agents, Azure SDK), breakage on a supported Python version, and security, credential-leak, data-loss, resource-leak, or concurrency problems.
Stay silent about everything else. In particular, do not comment on formatting,
naming, or docstring wording that ruff and mypy already enforce; do not
restate what the diff does; do not raise pre-existing issues the change merely
touches; and do not suggest refactors that are not required for correctness.
Returning no comments on a correct change is a good review — never manufacture
findings to look thorough.
Copilot code review never sees **/*.lock, **/*.svg, **/*.log, or
**/dist/**, so uv.lock is invisible to you. Excluded files are also stripped
from the file list you receive, so you cannot tell a lockfile that was never
updated from one that was updated and hidden from you. Never write a finding
about lockfile contents or lockfile presence; instead, see the lockfile
gotcha below.
libs/<package>/.
Treat each package as an independent review.AGENTS.md or .github/copilot-instructions.md along the changed path. The
repository root AGENTS.md is already in your context; do not re-derive it.Read the file for each package that changed. Skip the rest.
| Changed path | Package | Read |
|---|---|---|
libs/azure-ai/ | langchain-azure-ai | azure-ai.md |
libs/azure-compute/ | langchain-azure-compute | azure-compute.md |
libs/azure-cosmosdb/ | langchain-azure-cosmosdb | azure-cosmosdb.md |
libs/azure-postgresql/ | langchain-azure-postgresql | azure-postgresql.md |
libs/azure-storage/ | langchain-azure-storage | azure-storage.md |
libs/sqlserver/ | langchain-sqlserver | sqlserver.md |
libs/azure-dynamic-sessions/ | deprecated | azure-dynamic-sessions.md |
.github/, samples/, root docs | repo infrastructure | repo-infrastructure.md |
Also read ecosystem contracts when the change implements or overrides a LangChain, LangGraph, or Deep Agents base class, and Azure SDK contracts when it constructs an Azure client, handles credentials, or maps service errors.
These are the mistakes that pass local review and break later. They are specific to this repository and override any general instinct.
uv.lock. CI runs uv lock --check on
every touched package and fails the PR if a lockfile is stale or absent, so
this is already gated far more reliably than you can infer it. You cannot
observe lockfiles: they are excluded from your view and omitted from the
file list you receive. A reviewed-file count below the PR's total changed-file
count (for example "30/37 files reviewed") means excluded files exist, and on
a dependency change those are almost always the very uv.lock updates you
would otherwise flag as missing. Absence of evidence here is not evidence of
absence — stay silent and let CI decide.requires-python makes older runtimes resolve to the previous release rather
than install an incompatible one, so nothing breaks silently. These ship as
patch releases; demanding a **[Breaking change]:** marker on one
contradicts the version being shipped. Do not ask for that marker on a
support-policy change — see
release-notes for the classification rules.langchain-azure-compute enforces 100% coverage (fail_under = 100).
A new uncovered branch there fails CI, so a new if or except without a
test is a real finding in that package only.langchain-azure-ai lazy imports must be updated in three places — the
TYPE_CHECKING import, __all__, and _module_lookup. Updating fewer makes
the symbol import-time-invisible or __all__-inconsistent, and unit tests
catch only some of these.azure-ai and
azure-dynamic-sessions use their own _api.base (deprecated,
experimental); the other packages use langchain_core._api (beta,
deprecated). Do not flag one package for using the other's convention.USER_AGENT, _user_agent,
get_user_agent, with_user_agent). A new client path that omits it
silently drops partner telemetry attribution.asyncio_mode = "auto" in every package: async tests need no
@pytest.mark.asyncio. Do not ask for it.--strict-markers and --strict-config are set: a new pytest.mark.*
must be registered in that package's pyproject.toml or collection fails.azure-cosmosdb's local instructions still describe poetry, but its
Makefile and CI use uv run --frozen. The Makefile is authoritative;
do not flag correct uv usage there.azure-postgresql's local instructions ask for Sphinx-style docstrings
while its ruff config sets pydocstyle convention to google. Follow the
style already used in the file being changed and raise no docstring-style
findings in that package.azure-ai enforces this with
pytest-socket; the same expectation applies everywhere. A new unit test that
reaches a live service is a finding.Copilot code review labels comments High, Medium, or Low. Use that vocabulary.
If a finding does not clear the Low bar, leave it out.
Keep each comment to the smallest useful line range and this shape:
[Severity] Short imperative title
What breaks, and the specific input or code path that triggers it. Which contract or package rule it violates. One concrete suggested fix, only when it is short and unambiguous.
Cite the contract by name (for example, "VectorStore.get_by_ids must not
raise for missing IDs") rather than linking to documentation, and prefer one
precise sentence over a paragraph of hedging.
© langchain-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 10 other files (references) in .github/skills/code-review of langchain-ai/langchain-azure.
Open the folder on GitHubat commit 5784474
Code Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Code Review this skilllangchain-ai/langchain-azure | 147 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Agent Prompt Engineeringagentailor/fullstack-langgraph-nextjs-agent | 132 | — | ~3.6k | Automated safety check: Pass | MIT | |
| Agent Eval Casesagentailor/fullstack-langgraph-nextjs-agent | 132 | — | ~5.3k | Automated safety check: Pass | MIT | |
| Deep Agents to Pydantic AI Migrationpydantic/pydantic-ai | 20k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Chat Gun Backend ContractHsienW/chat-gun | 143 | — | ~2.1k | Automated safety check: Pass | Custom licence | |
| Mem0 Platform SDKmem0ai/mem0 | 67k | 1 repos | ~1.9k | Automated safety check: Pass | Apache-2.0 |
agentailor/fullstack-langgraph-nextjs-agent
Comprehensive guide for designing, refining, and auditing system prompts for autonomous AI agents based on Anthropic's production practices.
agentailor/fullstack-langgraph-nextjs-agent
Decide which AI agent behaviors are worth an eval case, then write those cases — harness-, framework-, and language-agnostic.
pydantic/pydantic-ai
Migrates Python LangChain Deep Agents applications to Pydantic AI and Pydantic AI Harness while preserving the application's observed behavior.
HsienW/chat-gun
Apply when creating, modifying, refactoring, debugging, testing, or reviewing TypeScript, LangGraph JS, LangChain, provider adapter, tool, MCP, prompt, state, checkpoint, runtime event, or backend…
mem0ai/mem0
Adds persistent memory to AI apps with the Mem0 Python and TypeScript SDKs: store, search, update and delete user memories, with framework integrations.
ComposioHQ/awesome-claude-skills
Debugs LangChain and LangGraph agents by pulling recent execution traces with the langsmith-fetch CLI and reporting errors, tool calls, timings and token use.
langchain-ai/langchain-azure
Skill for compiling and writing release notes for langchain-azure packages.
Categories
Reviews changes in the langchain-azure monorepo using package-specific knowledge of langchain-azure-ai, langchain-azure-compute, langchain-azure-cosmosdb, langchain-azure-postgresql…. Code Review is an agent skill from langchain-ai/langchain-azure, published by the product's own GitHub organization. Reviews changes in the langchain-azure monorepo using package-specific knowledge of langchain-azure-ai, langchain-azure-compute, langchain-azure-cosmosdb, langchain-azure-postgresql, langchain-azure-storage, langchain-sqlserver, and langchain-azure-dynamic-sessions, together with the LangChain, LangGraph, Deep Agents, and Azure SDK contracts each package must satisfy.
Code Review fits situations like: reviewing a pull request; checking code for bugs; assessing changes under libs/; .github/ in this repository.
Run `npx skills add langchain-ai/langchain-azure --skill code-review -a claude-code`. Or copy the skill folder (.github/skills/code-review in langchain-ai/langchain-azure) into .claude/skills/code-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add langchain-ai/langchain-azure --skill code-review -a codex`. Or copy the skill folder (.github/skills/code-review in langchain-ai/langchain-azure) into .agents/skills/code-review in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add langchain-ai/langchain-azure --skill code-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review, .gemini/skills/code-review, .github/skills/code-review and .opencode/skills/code-review in your project.
Going by SKILL.md and its folder, Code Review needs the command-line tools its instructions call (uv). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Code Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.2k 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 11k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Code Review: Agent Prompt Engineering (agentailor/fullstack-langgraph-nextjs-agent, 132 stars), Agent Eval Cases (agentailor/fullstack-langgraph-nextjs-agent, 132 stars), Deep Agents to Pydantic AI Migration (pydantic/pydantic-ai, 20k stars) and Chat Gun Backend Contract (HsienW/chat-gun, 143 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
langchain-ai (a GitHub organization, an official publisher) maintains it in langchain-ai/langchain-azure, which has 147 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 6, 2026.
Source: langchain-ai/langchain-azure on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.