Report · marked 10 Oct 2026

docling-project/docling

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

Python · 68,619 stars · 1,868 files · branch main

88 /100 A

Instructions 27/27Whether the repo tells an agent how to behave before it starts guessing. Full marks.Setup 14/20Whether an agent can install the project and get it running without a human. Losing marks on environment config and 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 15/20Whether 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

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.

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.

4,100 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 14/20 B+

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

✓Deterministic install 6/6

uv.lock pins the dependency tree.

Found uv.lock

✓Discoverable commands 6/6

Commands are declared where an agent will look for them.

Makefile

pyproject.toml scripts

scripts/ directory

✗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 2/2

dockerfile 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

1286 test files against 548 source files.

e.g. tests/__init__.py, tests/conftest.py, tests/data/afp/groundtruth/synthetic.afp.json

✓Test command is discoverable 7/7

An agent can find and run `make test`.

✓Continuous integration 4/4

14 GitHub Actions workflows define what "passing" means.

✓Lint and format rules 3/3

pyproject.toml 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 15/20 B+

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 196 patterns.

✗File sizes fit in context 4/6

3 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.

docling/backend/html_backend.py — 214KB

docling/backend/msword_backend.py — 185KB

tests/test_service_client_sdk_unit.py — 146KB

✗Repository weight 2/5

About 431MB 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 docling-project/docling

# AGENTS.md

Get your documents ready for gen AI

## Setup

```
uv sync
```

## Commands

```
make help
make setup
make hooks-install
make check           # lint and type check
make check-all
make validate
```

## Layout

- `docling/` 280 source files
- `tests/`   195 source files
- `docs/`    52 source files
- `scripts/` 4 source files
- `perfs/`   3 source files

## Conventions

- Tests live alongside the code they cover, following `tests/__init__.py`.
- CI defines what passing means. See `.github/workflows/ai-pr-triage.yml`, and keep it green.
- TODO: add the two or three conventions a newcomer always gets wrong here.

## Gotchas

- `docling/backend/html_backend.py` is 214KB. It will not fit comfortably in context, so read it in parts.

---

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/docling-project/docling.md

A draft gets the commands right and stops at the things only a maintainer knows. What a good Python AGENTS.md looks like covers what to add by hand, and what AGENTS.md is explains the format itself.

Show the mark

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[![agent ready](https://agentreadme.com/badge/docling-project/docling.svg)](https://agentreadme.com/docling-project/docling)

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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.

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