Report · marked 25 Aug 2026

langflow-ai/langflow

Ready for an agent to work in without hand-holding.

Python · 153,679 stars · 9,601 files · branch main

86 /100 A

Instructions 27/27Whether the repo tells an agent how to behave before it starts guessing. Full marks.Setup 18/20Whether an agent can install the project and get it running without a human. Losing marks on pinned runtime version.Verification loop 24/25Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy. Losing marks on 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

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.

Repository weight

Large binaries and vendored trees slow every operation an agent performs. Git LFS or a separate assets repo keeps the working tree navigable.

Pinned runtime version

Add a .nvmrc, .python-version, or equivalent so the agent's toolchain matches yours.

The full marking

Every deduction below names the file or setting it came from.

Instructions 27/27 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.

11,708 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 3/3

README has a clear getting-started section.

Setup 18/20 A

Whether an agent can install the project and get it running without a human.

✓Deterministic install 6/6

package-lock.json pins the dependency tree.

Found package-lock.json

✓Discoverable commands 6/6

Commands are declared where an agent will look for them.

Makefile

scripts/ directory

✓Environment config 4/4

.env.example documents what the app needs to 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 2/2

.devcontainer/devcontainer.json gives a known-good environment.

Verification loop 24/25 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

2613 test files against 7312 source files.

e.g. .github/workflows/ci-scripts-test.yml, .github/workflows/cross-bundle-test.yml, .github/workflows/cross-platform-test.md

✓Test command is discoverable 7/7

An agent can find and run `pytest`.

✓Continuous integration 4/4

49 GitHub Actions workflows define what "passing" means.

✓Lint and format rules 3/3

.eslintrc.json encodes the house style.

✗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 172 patterns.

✗File sizes fit in context 0/6

27 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.

src/frontend/src/icons/Azure/Azure.jsx — 446KB

src/frontend/src/icons/Listennotes/listennotes.jsx — 420KB

src/frontend/src/icons/VectaraIcon/Vectara.jsx — 406KB

✗Repository weight 0/5

About 1490MB 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 — drafted for langflow-ai/langflow

# AGENTS.md

Langflow is a powerful tool for building and deploying AI-powered agents and workflows.

## Setup

```
npm ci
```

## Commands

```
make check_tools
make help
make reinstall_backend
make install_backend
make init
make clean_python_cache
```

## Layout

- `src/`     6192 source files
- `docs/`    1031 source files
- `scripts/` 82 source files
- `docker/`  4 source files

## Conventions

- Tests live alongside the code they cover, following `.github/workflows/ci-scripts-test.yml`.
- CI defines what passing means. See `.github/workflows/a11y-scan.yml`, and keep it green.
- TODO: add the two or three conventions a newcomer always gets wrong here.

## Gotchas

- `src/frontend/src/icons/Azure/Azure.jsx` is 446KB. It will not fit comfortably in context, so read it in parts.
- Copy `.env.example` before running anything that needs configuration.

---

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/langflow-ai/langflow.md

Show the mark

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