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 0xDarkMatter/claude-mods --skill pypi-opsgit clone --depth 1 https://github.com/0xDarkMatter/claude-modsWrote 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/0xdarkmatter/claude-mods/pypi-ops)<a href="https://agentmods.dev/skills/0xdarkmatter/claude-mods/pypi-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/pypi-ops/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/0xdarkmatter/claude-mods/pypi-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/pypi-ops.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 | $0.00074 | $0.03169 |
| Opus 5 | $0.00037 | $0.01584 |
| Sonnet 5 | $0.00015 | $0.00634 |
| Haiku 4.5 | $0.00007 | $0.00317 |
Grade A, and why
pypi-ops 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 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.
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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PyPI Operations
Publish Python packages to PyPI on the 2026 best-practice path: OIDC Trusted
Publishing with signed PEP 740 attestations, no long-lived token to leak. This
skill owns the publish layer (the registry handshake, the first-publish
gotchas, the recovery playbook). General GitHub Actions syntax is ci-cd-ops;
the install-side worm defense is supply-chain-defense; gh/release-page
mechanics are github-ops.
Where this fits — the release pipeline
A release spans several skills; pypi-ops owns the registry step. Chain them:
- Vet dependencies before cutting a release —
supply-chain-defense(cooldown + behavioural scan). The build runs dependency code before it touches your publish credential, so a poisoned build dep can steal the token. - Preflight —
scripts/publish-preflight.sh --build .(this skill). - Bump → tag → push —
git-ops(its push-gate scans for secrets / forbidden files before the tag goes up). - CI publishes via OIDC — this skill's
assets/publish.yml; you approve at thepypienvironment gate. - Release page (optional, GitHub) —
github-ops, human-reviewed notes.
The one decision: OIDC vs API token
Default to OIDC Trusted Publishing. Reach for a token only when OIDC is impossible (publishing from a non-supported CI, or a one-off local push).
| Trusted Publishing (OIDC) ← default | API token | |
|---|---|---|
| Secret stored | None — short-lived OIDC token minted per run | Long-lived pypi-… token in a secret |
| Leak/phish blast radius | None to steal | Full publish rights until rotated |
| Provenance | PEP 740 attestations (signed, verifiable) | None by default |
| Setup | One-time publisher registration on PyPI | Generate token + store secret |
| Best for | All CI/CD releases | Legacy CI, emergency local upload |
If a repo currently uses a token, migrating to OIDC is strictly an upgrade — see references/trusted-publishing.md.
What ships with it
8 files 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.
- assets/publish.yml 4.4 KB
- references/recovery-playbook.md 5.1 KB
- references/trusted-publishing.md 4.7 KB
- references/uv-publish.md 2.9 KB
- scripts/check-action-pins.py 6.2 KB runs code
- scripts/diagnose-publish.sh 6.7 KB runs code
- scripts/publish-preflight.sh 10 KB runs code
- tests/run.sh 7.1 KB runs code
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 · 242 lines · 74 tokens per session scan A d481bafc6ca5
pypi-ops is a skill published in the GitHub repository 0xDarkMatter/claude-mods (35 stars, last pushed 17d ago), licensed MIT. It adds 74 tokens to every session and 3,169 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
ai-ml-development
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.
python-logging-best-practices
Python logging with loguru, structlog, and orjson. TRIGGERS - loguru, structlog, structured logging.
python-memory-safe-scripts
Memory-safe Python script patterns for long-running processes under systemd MemoryMax constraints. Covers allocator purge (mimalloc/glibc malloctrim), HTTP response lifecycle, DataFrame cleanup, thread-local connection reuse, and periodic GC cadence. Battle-tested through 5 OOM optimization cycles on production GPU…
pypi-doppler
LOCAL-ONLY PyPI publishing with Doppler credentials. TRIGGERS - publish to PyPI, pypi upload, local publish. NEVER use in CI/CD.
python-workspace
Python workspace for MQL5 integration. TRIGGERS - MetaTrader 5 Python, mt5 package, MQL5-Python setup.
claude-agent-sdk
Expert implementation guidance for the Claude Agent SDK (Python). Use when users are building with the Agent SDK — creating custom tools, managing sessions, controlling permissions, streaming responses, integrating MCP servers, adding hooks, defining subagents, or deploying SDK-based agents. Also use for SDK…