Report · marked 10 Oct 2026

K-Dense-AI/scientific-agent-skills

Solid foundations, held back in a few specific places.

Python · 48,262 stars · 2,780 files · branch main

82 /100 A-

Instructions 27/27Whether the repo tells an agent how to behave before it starts guessing. Full marks.Setup 6/14Whether an agent can install the project and get it running without a human. Losing marks on deterministic install and pinned runtime version.Verification loop 19/25Whether 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 17/20Whether the repo fits in a context window, or fights it. Losing marks on 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

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.

Lint and format rules

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

A type checker gives an agent an error message instead of a runtime surprise. It's the second-fastest feedback loop after the compiler.

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.

✓Instruction quality 12/12

Specific enough that an agent can act on it.

18,439 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 6/14 C

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.

scripts/ directory

–Environment config n/a

Not applicable — this reads as a library, with no environment to configure.

✗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 19/25 B+

Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy.

✓Tests exist 8/8

371 test files against 776 source files.

e.g. skills/pptx-posters/references/manifest_spec.md, tests/13c-metabolic-flux/evals.json, tests/13c-metabolic-flux/evaluation.md

✓Test command is discoverable 7/7

An agent can find and run `pytest`.

✓Continuous integration 4/4

5 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 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 12 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 473MB 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 K-Dense-AI/scientific-agent-skills

# AGENTS.md

Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 250,000+ scientists worldwide. 177 ready-to-use validated skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.

## Setup

```
# TODO: the install command. No lockfile was found, so this could not be inferred.
```

## Commands

```
pytest   # run the test suite
```

## Layout

- `skills/`  536 source files
- `tests/`   237 source files
- `scripts/` 1 source file

## Conventions

- Tests live alongside the code they cover, following `skills/pptx-posters/references/manifest_spec.md`.
- CI defines what passing means. See `.github/workflows/pr-skill-scan.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/K-Dense-AI/scientific-agent-skills.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.

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[![agent ready](https://agentreadme.com/badge/K-Dense-AI/scientific-agent-skills.svg)](https://agentreadme.com/K-Dense-AI/scientific-agent-skills)

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Think this mark is wrong?

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