Report · marked 26 Aug 2026
apachecn/ailearning
An agent is close to flying blind in this repository.
Python · 42,485 stars · 1,912 files · branch master
29
/100
F
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
2/20Whether an agent can install the project and get it running without a human. Losing marks on deterministic install and discoverable commands.Verification loop
4/25Whether 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 test command is discoverable.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
7/10How quickly anything new can orient itself. Losing marks on 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
Test command is discoverable
Add a `test` script or a `test` target that runs the whole suite with no arguments. The convention is the interface — an agent tries `npm test` and `make test` before it tries reading your CI config.
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 2/20 F
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
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
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 4/25 F
Whether an agent can check its own work. This is the category that most decides whether agent output is trustworthy.
✗Tests exist
4/8
7 test files against 151 source files.
Coverage is thin enough that an agent can break real behavior and still see green.
e.g. src/py3.x/ml/16.RecommenderSystems/sklearn-RS-demo-cf-item-test.py, src/py3.x/ml/16.RecommenderSystems/test_evaluation_model.py, src/py3.x/ml/16.RecommenderSystems/test_graph-based.py
✗Test command is discoverable
0/7
There's no obvious way to run the tests. Even if tests exist, an agent won't reliably find the entry point.
Add a `test` script or a `test` target that runs the whole suite with no arguments. The convention is the interface — an agent tries `npm test` and `make test` before it tries reading your CI config.
✗Continuous integration
0/4
No CI config. Nothing outside a developer's laptop enforces correctness.
A CI workflow doubles as machine-readable documentation: it's the one file that states, unambiguously, the exact commands that must succeed.
✗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 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 65 patterns.
✗File sizes fit in context
4/6
1 source file is 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.
asset/docsify-katex.js — 246KB
✗Repository weight
2/5
About 171MB 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 AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2 ## Setup ``` # TODO: the install command. No lockfile was found, so this could not be inferred. ``` ## Commands ``` # TODO: nothing declares a build or test command, so an agent has to guess. # This is the single most valuable section of this file. Fill it in. ``` ## Layout - `src/` 131 source files - `asset/` 11 source files - `tutorials/` 5 source files - `old/` 2 source files ## Conventions - Tests live alongside the code they cover, following `src/py3.x/ml/16.RecommenderSystems/sklearn-RS-demo-cf-item-test.py`. - TODO: add the two or three conventions a newcomer always gets wrong here. ## Gotchas - `asset/docsify-katex.js` is 246KB. 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/apachecn/ailearning.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.