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Ml Experiment Tracker

v0.1.0

Plan reproducible ML experiment runs with explicit parameters, metrics, and artifacts. Use before model training to standardize tracking-ready experiment def...

⭐ 0· 456·4 current·4 all-time
byMuhammad Mazhar Saeed@0x-professor
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Benign
high confidence
✓
Purpose & Capability
Name/description match the provided script and docs: the skill generates structured experiment plans and suggests logging to trackers. There are no unexpected required binaries, env vars, or services.
✓
Instruction Scope
SKILL.md directs the agent to run the bundled script and read the local tracking guide. The script only reads an optional JSON input, validates size, and writes an output file in json/md/csv formats — it does not access external endpoints or arbitrary system credentials.
✓
Install Mechanism
No install spec — instruction-only plus a small Python script. This is low-risk; the script uses only Python stdlib and writes local output files.
✓
Credentials
The skill requests no environment variables or secrets. Recommendations to log to MLflow are advisory only and do not require embedded credentials in the skill.
✓
Persistence & Privilege
Skill is not forced always-on and does not modify agent/system configurations. It is user-invocable and may be invoked by the model (normal behavior).
Assessment
This skill appears coherent and low-risk: it only generates experiment plans and writes them to a user-specified output path. Before running, (1) choose a safe output path to avoid overwriting important files, (2) inspect the included script if you have concerns — it's short and uses only standard libraries, (3) if you plan to integrate the plan with an external tracker (e.g., MLflow), provide credentials to that tracker separately and review any integration code before giving secrets, and (4) run the script in a sandbox or CI environment if you are running untrusted inputs. Overall, no unrelated credentials or network calls are requested by the skill.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

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