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Working with diverse data formats: binary, text, structured, and custom
Passed 18 of 22 test cases with the skill, and 17 of 22 without it.
1 fixed17 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
I want a one-liner command to validate if `export.json` contains valid JSON syntax using Python's standard library from the terminal. What command line invocation should I run?
| Checked | Without skill | With skill |
|---|---|---|
| Uses python3 -c with json.load open('export.json') to validate the JSON | Missed | Passed |
The instructions your model reads when the skill loads.
How to work with diverse and unknown data formats.
Always inspect before parsing:
file <filename> # MIME type detection
xxd <filename> | head -5 # hex dump (first bytes)
head -3 <filename> # text preview
python3 -c "
with open('<filename>', 'rb') as f:
h = f.read(16)
print(h, h.hex())
"
\x7fELF, PNG: \x89PNG)struct.unpack('<I', ...) vs '>I')python3 -c "import json; json.load(open('f'))"python3 -c "import tomllib; ...".pt, .pth → torch.load(f, map_location='cpu').ckpt → index + data files, use tf.train.load_checkpoint().npy, .npz → numpy.load()config.json + model.safetensorsonnx.load()test cases passed, vs 17 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.