Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sawrus/agent-guides --skill experiment-trackinggit clone --depth 1 https://github.com/sawrus/agent-guidesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sawrus/agent-guides/experiment-tracking)<a href="https://agentmods.dev/skills/sawrus/agent-guides/experiment-tracking"><img src="https://agentmods.dev/badge/skills/sawrus/agent-guides/experiment-tracking/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sawrus/agent-guides/experiment-tracking"><img src="https://agentmods.dev/badge/skills/sawrus/agent-guides/experiment-tracking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00233 |
| Opus 5 | $0.00000 | $0.00117 |
| Sonnet 5 | $0.00000 | $0.00047 |
| Haiku 4.5 | $0.00000 | $0.00023 |
Grade A, and why
experiment-tracking scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
"git_commit": subprocess.check_output(["git", "rev-parse", "HEAD"]).decode().strip(), What it actually says
Skill: Experiment Tracking (MLflow)
When to load
When running training experiments, comparing runs, or reproducing a historical experiment.
MLflow Tracking Pattern
with mlflow.start_run(run_name="xgboost-lr-0.01-depth-6") as run:
mlflow.log_params({
"model_type": "xgboost",
"learning_rate": 0.01,
"max_depth": 6,
"data_version": dataset_version,
"random_seed": 42,
})
mlflow.set_tags({
"git_commit": subprocess.check_output(["git", "rev-parse", "HEAD"]).decode().strip(),
})
model = train_model(X_train, y_train, hyperparams)
mlflow.log_metrics({"test_auc_roc": 0.847, "test_f1": 0.731})
signature = mlflow.models.infer_signature(X_train, model.predict(X_train))
mlflow.xgboost.log_model(model, "model", signature=signature)
mlflow.log_artifact("evaluation_scorecard.json")
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 30 lines · 0 tokens per session scan A ae6d5dcd97e0
experiment-tracking is a skill published in the GitHub repository sawrus/agent-guides (17 stars, last pushed 9d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 233 tokens. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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