Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add yale-som-hpc/claude-code-marketplace/plugin install hpcWrote 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/yale-som-hpc/claude-code-marketplace/coding-in-python)<a href="https://agentmods.dev/skills/yale-som-hpc/claude-code-marketplace/coding-in-python"><img src="https://agentmods.dev/badge/skills/yale-som-hpc/claude-code-marketplace/coding-in-python/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/yale-som-hpc/claude-code-marketplace/coding-in-python"><img src="https://agentmods.dev/badge/skills/yale-som-hpc/claude-code-marketplace/coding-in-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00060 | $0.00893 |
| Opus 5.5 | $0.00024 | $0.00357 |
| Sonnet 5.5 | $0.00012 | $0.00179 |
| Haiku 4.5 | $0.00006 | $0.00089 |
Grade A, and why
coding-in-python scanned grade A with 0 findings 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 2mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coding in Python
Rule: locked env, portable paths, thin notebooks, runnable scripts.
For cluster execution, also load running Python.
Defaults
uvfor envs and lockfiles. Commitpyproject.tomlanduv.lock; ignore.venv/.rufffor format + lint.pathlibfor paths.argparsefor scripts. Useclickonly for real subcommands.logging, not scatteredprint(), for long runs.pytestfor reusable logic; smoke tests for analysis scripts.
uv init --app
uv add polars pyarrow duckdb pandas statsmodels
uv add --dev ruff pytest
uv sync --frozen
On HPC: sync/setup before large jobs. For long Slurm jobs call .venv/bin/python directly; see running Python.
Layout
project/
├── pyproject.toml
├── uv.lock
├── README.md
├── scripts/ # entry points
├── src/ # shared helpers, or lib.py for tiny projects
├── notebooks/ # exploration
├── data/raw/ # immutable; usually ignored
├── data/derived/ # rebuildable
└── results/ # figures/tables/logs
Paths
Never commit laptop/user paths: /Users/..., C:\Users\..., /home/netid/..., /gpfs/scratch60/netid/....
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
DATA = REPO / "data" / "raw" / "panel.parquet"
For scripts, accept paths as args:
import argparse
from pathlib import Path
parser = argparse.ArgumentParser()
parser.add_argument("--input", type=Path, required=True)
parser.add_argument("--output", type=Path, required=True)
args = parser.parse_args()
Style
- f-strings.
- Imports at top.
- Type hints on public/helper function signatures.
@dataclass(frozen=True)for small immutable records.pydanticonly for external/untrusted input.- Context managers for every file/network/DB handle.
- Early returns to reduce nesting.
- Fixed seeds:
rng = np.random.default_rng(42); passrngthrough.
Logging
import logging
log = logging.getLogger(__name__)
def main() -> None:
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(levelname)s %(name)s: %(message)s",
)
log.info("starting")
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.
- 2mo ago First seen · 132 lines · 60 tokens per session scan A 9e8637b4ac43
coding-in-python is a skill published in the GitHub repository yale-som-hpc/claude-code-marketplace (5 stars, last pushed 3mo ago), licensed Unlicense. It adds 60 tokens to every session and 893 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
coding-in-python compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| coding-in-pythonyale-som-hpc/claude-code-marketplace | Skill | 5 | 3mo ago | Unlicense | A | 60 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| pennylaneK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 74 | Claude Code |
| holoscan-install-wheelNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 34 | Claude Code, Codex |
| future-self-liteTHU-MAIC/OpenMAIC | Skill | 43k | yesterday | MIT | A | 20 | Claude Code, Codex |
| rocm-kernelshuggingface/kernels | Skill | 783 | yesterday | Apache-2.0 | A | 93 | Claude Code |
| typing-exclusion-workergetsentry/skills | Skill | 1.1k | yesterday | Apache-2.0 | A | 57 | Claude Code |