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/saaspegasus/django-skills/upgrade-python-depsnpx skills add saaspegasus/django-skills --skill upgrade-python-depsgit clone --depth 1 https://github.com/saaspegasus/django-skillsWrote 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/saaspegasus/django-skills/upgrade-python-deps)<a href="https://agentmods.dev/skills/saaspegasus/django-skills/upgrade-python-deps"><img src="https://agentmods.dev/badge/skills/saaspegasus/django-skills/upgrade-python-deps.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00553 |
| Opus 5 | $0.00000 | $0.00277 |
| Sonnet 5 | $0.00000 | $0.00111 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
upgrade-python-deps 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 4d 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.
This is a copy
100% identical to upgrade-python-deps — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Your task
Upgrade all Python dependencies and verify nothing is broken.
Step 1: Upgrade the lock file
Run uv lock --upgrade --exclude-newer "7 days" to upgrade all dependencies to their latest compatible
versions (with a 7-day cooldown to mitigate supply-chain attacks).
Review the output for any resolution errors. If there are conflicts, report them to the user and ask how to proceed before continuing.
Step 2: Remove the cooldown marker from the lock file
uv records the --exclude-newer cutoff inside uv.lock as project configuration. Since it
isn't declared in pyproject.toml, any later uv sync or uv run sees a config mismatch,
discards the lockfile, and silently re-resolves everything to the newest versions — undoing
the cooldown. Prevent this by deleting the [options] block at the top of uv.lock
(the exclude-newer / exclude-newer-span lines) before syncing:
sed -i '/^\[options\]$/,/^$/d' uv.lock
The cooldown-resolved versions stay in place; only the marker is removed. Verify with
grep exclude-newer uv.lock (should print nothing).
Step 3: Sync the environment
Run uv sync to install the upgraded dependencies into the virtual environment.
Step 4: Run post-upgrade checks
Run these checks sequentially, stopping if any step fails:
- Type checking: Run
uv run mypy .and report any new type errors. These may be caused by updated type stubs or changes in library APIs. - Tests: Run
make testto verify the test suite still passes.
Step 5: Summarize and commit
Summarize what was done:
- Which packages were upgraded (notable version changes)
- Whether any type errors were introduced
- Whether all tests passed
- Any issues that need manual attention
If there were failures, present the issues and ask how the user wants to proceed.
If everything passed, ask the user if they'd like to commit the changes. If yes, commit
using the /commit skill.
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.
- 4d ago First seen · 64 lines · 0 tokens per session scan A d0f49210dcc6
upgrade-python-deps is a skill published in the GitHub repository saaspegasus/django-skills (30 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 553 tokens. A static security scan graded it A with 0 findings. It is 100% identical to upgrade-python-deps, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
pennylane
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…
dd-code-generation
Use pup CLI for immediate Datadog operations or generate code for integration into applications.
rocm-kernels
Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline…
holoscan-install-wheel
Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.
typing-exclusion-worker
Python typing exclusion worker: remove assigned mypy exclusion modules in small scoped batches, fix typing issues, run validation, and produce a structured completion summary. Use when running parallel typing-debt workers or when asked to remove modules from pyproject mypy exclusion overrides.