Report · marked 25 Aug 2026
Pythagora-io/gpt-pilot
An agent will struggle here, mostly for fixable reasons.
Python · 33,686 stars · 518 files · branch main
50
/100
C+
Instructions
2/27Whether the repo tells an agent how to behave before it starts guessing. Losing marks on agent instruction file and instruction quality.Setup
7/20Whether an agent can install the project and get it running without a human. Losing marks on deterministic install and discoverable commands.Verification loop
20/25Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy. Losing marks on tests exist and static type checking.Context economy
17/20Whether the repo fits in a context window, or fights it. Losing marks on repository weight.Navigability
5/10How quickly anything new can orient itself. Losing marks on written documentation and license.
Higher is better. Accent marks what is costing you most.
Fix these first
01
Agent instruction file
Add an AGENTS.md at the root: what the project is, how to install, how to run, how to test, and the two or three conventions a newcomer always gets wrong.
02
Instruction quality
Instructions earn their keep by naming exact commands. 'Run the tests with `pnpm test`' beats three paragraphs of philosophy.
03
Discoverable commands
Declare the handful of commands that matter in package.json scripts, a Makefile, or a justfile. Naming them turns guesswork into a lookup.
The full marking
Every deduction below names the file or setting it came from.
Instructions 2/27 F
Whether the repo tells an agent how to behave before it starts guessing.
✗Agent instruction file
0/12
None found. Every agent that opens this repo starts from zero.
Add an AGENTS.md at the root: what the project is, how to install, how to run, how to test, and the two or three conventions a newcomer always gets wrong.
Looked for AGENTS.md, CLAUDE.md, .github/copilot-instructions.md, .cursorrules
✗Instruction quality
0/12
Nothing to judge, since there are no instructions.
Instructions earn their keep by naming exact commands. 'Run the tests with `pnpm test`' beats three paragraphs of philosophy.
✗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 7/20 D
Whether an agent can install the project and get it running without a human.
✗Deterministic install
3/6
Only requirements.txt, which pins loosely at best.
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
0/6
No declared commands. An agent has to infer how to build and run this from the file tree.
Declare the handful of commands that matter in package.json scripts, a Makefile, or a justfile. Naming them turns guesswork into a lookup.
✗Environment config
2/4
Env vars are mentioned in the README but there's no example file to copy.
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 20/25 A-
Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy.
✗Tests exist
6/8
48 test files against 329 source files.
e.g. core/db/migrations/versions/ff891d366761_add_example_project_to_spec.py, core/prompts/spec-writer/review_spec.prompt, tests/__init__.py
✓Test command is discoverable
7/7
An agent can find and run `pytest`.
✓Continuous integration
4/4
2 GitHub Actions workflows define what "passing" means.
✓Lint and format rules
3/3
pyproject.toml encodes the house style.
✗Static type checking
0/3
No static type checking.
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 17/20 A
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 24 patterns.
✓File sizes fit in context
6/6
No source file is large enough to crowd out a context window.
✗Repository weight
2/5
About 360MB 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 The first real AI developer ## Setup ``` pip install -r requirements.txt ``` ## Commands ``` pytest # run the test suite ruff check . # lint ``` ## Layout - `core/` 281 source files - `tests/` 44 source files - `cloud/` 3 source files ## Conventions - Tests live alongside the code they cover, following `core/db/migrations/versions/ff891d366761_add_example_project_to_spec.py`. - CI defines what passing means. See `.github/workflows/ci.yml`, and keep it green. - TODO: add the two or three conventions a newcomer always gets wrong here. ## Gotchas - 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/Pythagora-io/gpt-pilot.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.