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/cloudinary/pycloudinary/agents-mdgit clone --depth 1 https://github.com/cloudinary/pycloudinaryWhat 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 | $0.01326 | $0.01326 |
| Opus 5 | $0.00663 | $0.00663 |
| Sonnet 5 | $0.00265 | $0.00265 |
| Haiku 4.5 | $0.00133 | $0.00133 |
Grade A, and why
pycloudinary AGENTS.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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file is for agents contributing to this repository. If you are using the
installed cloudinary package in another project, read the bundled docs in the
installed package's cloudinary/docs/ directory instead.
Commands
pip install -e . # install for development
pip install tox pytest # test tooling
python -m pytest test # core test suite
python -m pytest test/test_uploader.py # a single module
tox # full matrix (Python 3.10-3.14, Django 4.2-6.0)
tox -e py312-core # one environment, as CI runs it
DJANGO_SETTINGS_MODULE=django_tests.settings \
django-admin test -v2 django_tests # Django integration suite
python -m build # build sdist + wheel
Every suite needs a working CLOUDINARY_URL in the environment — there is no
offline or mocked tier. CI allocates a throwaway cloud per job via
tools/get_test_cloud.sh; locally, export your own or provision one with
python -c "from cloudinary.provisioning import create_cloud; print(create_cloud())".
Testing
test/is the core suite and hits the live API. Tests namespace their assets withUNIQUE_TEST_IDfromtest/helper_test.pyand clean up after themselves — follow that pattern rather than leaving fixtures behind.django_tests/runs as a real Django app (django_tests.settings, in-memory sqlite). It coversCloudinaryField, the form fields, and migrations; the templatetags have no coverage yet.- Provisioning tests (
test/test_provisioning_api.py) additionally needCLOUDINARY_ACCOUNT_URL; they are skipped without it. - Add-on tests (
test/addon_types.py) require paid add-ons. Guard anything new with the existing skip decorators rather than making the default suite fail. - Nondeterministic AI output (auto-tagging, captioning, moderation verdicts) must be asserted by request shape, state transition, and response schema — never exact values.
- There is no lint tooling in this repo. Do not add a linter or reformat files wholesale as part of an unrelated change.
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 · 114 lines · 1,326 tokens per session scan A 9a90b751ab74
pycloudinary AGENTS.md is an instructions file published in the GitHub repository cloudinary/pycloudinary (262 stars, last pushed 5d ago), licensed MIT. It adds 1,326 tokens to every session, about $0.0066 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.
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