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 instructions/xiaoleiy/podpull/claude-mdgit clone --depth 1 https://github.com/xiaoleiy/podpullWhat 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 | $0.02049 | $0.02049 |
| Opus 5 | $0.01025 | $0.01025 |
| Sonnet 5 | $0.00410 | $0.00410 |
| Haiku 4.5 | $0.00205 | $0.00205 |
Grade A, and why
podpull CLAUDE.md 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 2d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Guidance for AI coding agents (and humans) working in the podpull repository.
This is the canonical agent guide; AGENTS.md points here.
What this is
podpull is a small command-line tool that downloads a specific podcast episode's
audio from an Apple Podcasts show/episode, a raw RSS feed, or a
xiaoyuzhou / 小宇宙 episode link.
The core idea: Apple Podcasts hosts no audio — it points at each show's RSS feed, where
every episode carries a direct <enclosure> URL. podpull walks that chain and downloads
the file. No login, no DRM.
Python ≥ 3.9. Published on PyPI (pipx install podpull)
and a Homebrew tap (brew install xiaoleiy/tap/podpull).
Layout
src/podpull/
__init__.py # __version__ lives here
__main__.py # `python -m podpull`
core.py # resolve/parse/search/select/download — PURE STDLIB, no third-party imports
cli.py # argparse commands + ALL UI (rich, questionary, rich-argparse)
skills.py # `podpull skills` — installs agent integrations
serve/ # `podpull serve` — stdlib HTTP metadata API + static UI
integrations/ # bundled skill/command/rule files (packaged as wheel data)
tests/ # test_core.py, test_cli.py, test_skills.py (pytest, no network)
docs/ # index.html (Aurora landing), HOSTING.md, icon.svg, demo.tape/demo.gif
public/ # generated by scripts/sync_web_public.py for Vercel (do not hand-edit)
api/ # Vercel Python metadata gateway (wraps serve.handle_api)
scripts/ # sync_web_public.py — docs/ + serve/static → public/
vercel.json # podpull.xiaolei.work deploy config
.github/workflows/ # ci.yml, publish.yml (PyPI), release.yml (Homebrew tap bump)
Load-bearing invariants — do NOT break these
core.pystays dependency-free. Only the Python standard library. All third-party deps (rich,questionary,rich-argparse) live incli.py. Network/parse/download logic is pure stdlib so it's easy to test and audit. If you need a UI concern in core, pass a callback (seedownload_url(..., on_progress=…)) rather than importing rich.- stdout = machine output, stderr = humans. Downloaded file paths print to stdout;
spinners, tables, progress bars, and messages go to stderr (rich
Console(stderr=True)). Keep it that way — people pipe/capture stdout. - Interactive picker vs. scripting.
podpull get <show>with no selector opens thequestionarymulti-select picker only when stdin+stderr are a TTY and--no-inputisn't set; otherwise it prints a listing + hint and exits non-zero (never hangs). - Cloud-/Windows-safe filenames.
core.safe_filenameNFKC-folds, drops emoji/symbols and control chars, strips OS-forbidden + full-width chars, trims edges, caps at 120, and avoids Windows reserved device names (CON,NUL, …). Preserve this when touching naming. - Browser User-Agent.
core.UAis a plain browser UA on purpose — xiaoyuzhou's CDN (feed.xyzfm.space) returns 403 to identifiable tool UAs. Don't "brand" it back. - All text file I/O is explicit
encoding="utf-8". Windows defaults to cp1252 and will raise on CJK otherwise (audio writes are binary — that's fine). - Multiple episodes → a per-show sub-folder (
<out>/<show name>/); a single episode lands directly in--out.
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.
- 2d ago First seen · 139 lines · 2,049 tokens per session scan A 28f480ff7791
podpull CLAUDE.md is an instructions file published in the GitHub repository xiaoleiy/podpull (141 stars, last pushed 1mo ago), licensed MIT. It adds 2,049 tokens to every session, about $0.0102 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 2026-08-30.
Other instructions, from other repositories
spotify-cli CLAUDE.md
Claude Code instructions for zcaceres/spotify-cli, covering spotify cli and code style.
Paperlab AGENTS.md
Instructions for NourMtir0722/Paperlab, covering paperlab — for coding agents, integrating paperlab into a project, stage mode — paper as architecture, content types and lighting is data, not an enum.
markdy-com copilot-instructions.md
Instructions for HoangYell/markdy-com, a project described as: 🎬 Open-source animated architecture diagrams as code. Diagram-native DSL, 17 layout engines, Web Animations API, and MCP server for AI agents.
diffusers AGENTS.md
AGENTS.md instructions for huggingface/diffusers, a project described as: 🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
comfy-prompt-studio AGENTS.md
Instructions for yxhpy/comfy-prompt-studio, covering agents.md - ai 代理配置文档, ai 提供商, 1. ollama (默认), 2. gemini and 提示词生成服务.
davinci-resolve-mcp AGENTS.md
Instructions for apvlv/davinci-resolve-mcp, covering project knowledge base, structure, where to look, code map and conventions.