Deep Agents is an extensible agent harness that provides an out-of-the-box agent for long, multi-step tasks, with features such as planning, sub-agents, filesystem access, context management, memory, and human approval of tool calls. It is used by developers building agents with different language models, and its catalogue entries extend the harness with reusable skills, MCP servers, and instructions.
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.
npx skills add langchain-ai/deepagents --skill code-reviewgit clone --depth 1 https://github.com/langchain-ai/deepagentsWrote 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.
[](https://agentmods.dev/skills/langchain-ai/deepagents/code-review)<a href="https://agentmods.dev/skills/langchain-ai/deepagents/code-review"><img src="https://agentmods.dev/badge/skills/langchain-ai/deepagents/code-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/langchain-ai/deepagents/code-review"><img src="https://agentmods.dev/badge/skills/langchain-ai/deepagents/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00424 |
| Opus 5.5 | $0.00009 | $0.00170 |
| Sonnet 5.5 | $0.00005 | $0.00085 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
code-review 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 1mo ago.
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.
What it actually says
Code Review Skill
Use this skill after implementing changes to validate your work before delivering.
Review Checklist
1. Correctness
- Changes solve the original issue/task
- No unintended side effects on existing functionality
- Edge cases are handled
- Error handling is appropriate (not excessive)
2. Code Quality
- Code matches existing style and patterns
- No unnecessary complexity or abstraction
- Variable and function names are clear
- No dead code, commented-out code, or TODOs left behind
3. Tests
- New functionality has test coverage
- Existing tests still pass
- Tests cover both happy path and error cases
- Tests are not brittle (don't test implementation details)
4. Safety
- No hardcoded secrets or credentials
- User input is validated at boundaries
- No SQL injection, XSS, or command injection vectors
- File operations use safe paths
Process
- Read each modified file end-to-end (not just the diff)
- Run the test suite:
execute("python -m pytest -v") - Run linters if available:
execute("ruff check .") - Run the bundled lint check:
execute("python /skills/code-review/lint_check.py .") - Check against each item in the review checklist
- If any issues found, fix them and re-review
- When everything passes, the review is complete
Helper Scripts
/skills/code-review/lint_check.py— Scans Python files for missing docstrings, long functions (>50 lines), and bareexcept:clauses. Run it viaexecute("python /skills/code-review/lint_check.py [path ...]").
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 51 lines · 23 tokens per session scan A 39271a17e19d
code-review is a skill published in the GitHub repository langchain-ai/deepagents (30,344 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 424 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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