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 agentmods add skills/fmind/dotfiles/python-scriptnpx skills add fmind/dotfiles --skill python-scriptgit clone --depth 1 https://github.com/fmind/dotfilesWhat 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 | $0.00034 | $0.00656 |
| Opus 5 | $0.00017 | $0.00328 |
| Sonnet 5 | $0.00007 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
python-script 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 yesterday.
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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PEP 723 Standalone Python Scripts
Write single-file Python CLI scripts with inline dependency metadata (PEP 723) executed via uv run — no virtualenv, no pyproject.toml, no project scaffolding required.
When to Use
- Agent scratch scripts (store in
.agents/tmp/). - Any situation where a full Python project is overkill.
- Quick automation, data processing, or one-off CLI tools.
Template
Base every script on script.py. Key elements:
- Shebang + PEP 723 block (must be at the top of the file):
#!/usr/bin/env -S uv run --quiet --script # /// script # requires-python = ">=3.14" # dependencies = [ # "rich>=15.0.0", # "typer>=0.27.0", # ] # /// - CLI framework: Use
TyperwithRichfor argument parsing and formatted output. - Dual consoles:
Console()for stdout results,Console(stderr=True)for logs/errors. - Typed arguments: Use
Annotated[..., typer.Argument/Option(...)]with help text. - Error handling: Catch exceptions at the CLI boundary with
err.print_exception(show_locals=False)and exit viaraise typer.Exit(code=1) from None; never render locals because they can contain secrets.
Execution
# Direct execution (after chmod +x)
./script.py input.txt
# Or via uv explicitly
uv run script.py input.txt --verbose
uv resolves and caches the declared dependencies automatically — no manual install step.
For a durable script, commit its adjacent lockfile so future runs reuse the same resolution:
uv lock --script script.py
uv run --locked --script script.py input.txt
Guidelines
- Pin
requires-pythonto the minimum version you need (e.g.,>=3.14). - Declare dependency lower bounds (e.g.,
rich>=15.0.0) for compatibility. Lower bounds alone are not reproducible; useuv lock --scriptfor a durable script. - Keep it single-file — if the script grows beyond ~200 lines or needs multiple modules, switch to a full project via the python-stack skill.
- No bare
except— outside the CLI boundary handler above (which prints the full traceback before exiting non-zero), let unexpected errors propagate.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 67 lines · 34 tokens per session scan A 1d7f16216072
python-script is a skill published in the GitHub repository fmind/dotfiles (4 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 656 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
dotfiles-bootstrap
Bootstrap a workstation with the dotfiles framework. Takes a GitHub user / owner+repo / explicit clone URL and runs dot init (which shells out to chezmoi) with the right safety prompts. Honors the active agent profile (ask / plan / apply / audit) so it defaults to dry-run in safer modes and full apply in apply.
vibe
Delegate a coding task to a cheap AI model (Mistral Vibe by default, but any provider Vibe knows about — DeepSeek, Gemini Flash, etc.) and supervise the result via git diff. Claude orchestrates, the cheap model codes. Claude consumes 500-1500 tokens per delegation regardless of how many file reads the delegate does…
aiq-research
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
obsidian-bases
Obsidian Bases database feature for YAML-based interactive note views. Use when creating .base files, writing filter queries, building formulas, configuring table/card views, or working with Obsidian properties and frontmatter databases.
telegram
Send notifications, interactive questions, or multiple-choice polls to the user via Telegram. Use when the user asks to be notified ("ping me", "notify me on Telegram", "ask me when..."), when a long-running task finishes and the user is likely away, when an irreversible action needs out-of-band confirmation, or when…
chezmoi-expert
Comprehensive chezmoi dotfiles management expertise including templates, cross-platform configuration, file naming conventions, and troubleshooting. Covers source directory management, reproducible environment setup, and chezmoi templating with Go templates. Use when user mentions chezmoi, dotfiles, cross-platform…