Report · marked 25 Aug 2026
langchain-ai/langgraph
Solid foundations, held back in a few specific places.
Python · 40,440 stars · 672 files · branch main
72
/100
B+
Instructions
26/27Whether the repo tells an agent how to behave before it starts guessing. Losing marks on readme as an entry point.Setup
6/18Whether an agent can install the project and get it running without a human. Losing marks on deterministic install and environment config.Verification loop
21/25Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy. Losing marks on lint and format rules and static type checking.Context economy
9/20Whether the repo fits in a context window, or fights it. Losing marks on file sizes fit in context and repository weight.Navigability
10/10How quickly anything new can orient itself. Full marks.
Higher is better. Accent marks what is costing you most.
Fix these first
01
Deterministic install
Commit the lockfile your package manager generates. Without it, an agent's install and your install are different builds, and 'works on my machine' becomes unfalsifiable.
02
File sizes fit in context
A single file that fills the context window forces an agent to work from fragments, and it will confidently edit code it never saw. Splitting the worst offenders pays for itself immediately.
03
Environment config
Add a .env.example listing every variable with a safe placeholder value. It's the cheapest possible fix and it unblocks the whole first run.
The full marking
Every deduction below names the file or setting it came from.
Instructions 26/27 A+
Whether the repo tells an agent how to behave before it starts guessing.
✓Agent instruction file
12/12
AGENTS.md is present, which is the format the most tools read.
Also found: CLAUDE.md
✓Instruction quality
12/12
Specific enough that an agent can act on it.
2,048 characters, a workable length
names the actual commands to run
uses headings, so an agent can skim it
includes copyable code blocks
✗README as an entry point
2/3
README exists but never explains how to get the thing running.
Give the README an Install and a Usage heading with real commands under each. Agents pattern-match on those headings.
Setup 6/18 D
Whether an agent can install the project and get it running without a human.
✗Deterministic install
0/6
No lockfile. An agent installing dependencies may not get what CI got.
Commit the lockfile your package manager generates. Without it, an agent's install and your install are different builds, and 'works on my machine' becomes unfalsifiable.
✓Discoverable commands
6/6
Commands are declared where an agent will look for them.
Makefile
✗Environment config
0/4
Nothing documents the environment this needs. An agent will get a runtime error it can't diagnose.
Add a .env.example listing every variable with a safe placeholder value. It's the cheapest possible fix and it unblocks the whole first run.
✗Pinned runtime version
0/2
No pinned runtime version.
Add a .nvmrc, .python-version, or equivalent so the agent's toolchain matches yours.
–Reproducible environment
n/a
Not applicable — a library doesn't need a container to be worked on.
Verification loop 21/25 A-
Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy.
✓Tests exist
8/8
239 test files against 461 source files.
e.g. .github/scripts/run_langgraph_cli_test.py, .github/workflows/_integration_test.yml, .github/workflows/_sdk_integration_test.yml
✓Test command is discoverable
7/7
An agent can find and run `make test`.
✓Continuous integration
4/4
17 GitHub Actions workflows define what "passing" means.
✗Lint and format rules
0/3
No linter or formatter config. Style is tribal knowledge, so agent output will drift from yours.
A formatter config is the cheapest way to stop reviewing whitespace in agent diffs. It moves style from opinion to a command.
✗Static type checking
2/3
Type checking is configured, but not in strict mode.
A type checker gives an agent an error message instead of a runtime surprise. It's the second-fastest feedback loop after the compiler.
Context economy 9/20 C
Whether the repo fits in a context window, or fights it.
✓No committed build output
6/6
No generated directories committed.
✓.gitignore hygiene
3/3
.gitignore covers 76 patterns.
✗File sizes fit in context
0/6
8 source files are over 100KB.
A single file that fills the context window forces an agent to work from fragments, and it will confidently edit code it never saw. Splitting the worst offenders pays for itself immediately.
libs/langgraph/tests/test_pregel.py — 302KB
libs/langgraph/tests/test_pregel_async.py — 302KB
libs/langgraph/tests/test_large_cases.py — 209KB
✗Repository weight
0/5
About 525MB checked out. Large enough that cloning and searching are both slow.
Large binaries and vendored trees slow every operation an agent performs. Git LFS or a separate assets repo keeps the working tree navigable.
Here is your AGENTS.md
Drafted from what is actually in this repository: the install
command from your lockfile, the commands you already declare, your real directory layout. Anything
marked TODO needs a person. Save it at the root as AGENTS.md.
# AGENTS.md Build resilient agents. ## Setup ``` # TODO: the install command. No lockfile was found, so this could not be inferred. ``` ## Commands ``` make install make lint # lint make format # format make lock make lock-upgrade make test # run the test suite, must pass before any commit ``` ## Layout - `libs/` 456 source files - `examples/` 2 source files - `docs/` 1 source file ## Conventions - Tests live alongside the code they cover, following `.github/scripts/run_langgraph_cli_test.py`. - CI defines what passing means. See `.github/workflows/_integration_test.yml`, and keep it green. - TODO: add the two or three conventions a newcomer always gets wrong here. ## Gotchas - `libs/langgraph/tests/test_pregel.py` is 302KB. It will not fit comfortably in context, so read it in parts. - No lockfile is committed, so an install here may not match what CI produced. --- Drafted by agentreadme.com from what is in this repository. Everything marked TODO needs a human. Check it in as AGENTS.md at the root.
Open the raw markdown
or
curl -o AGENTS.md agentreadme.com/draft/langchain-ai/langgraph.md
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Think this mark is wrong?
Every deduction above names the file it came from, so this can be settled by looking. If a check missed something, that is a rule worth fixing.