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/leynier/python-template/if-deploy_target-none-deploy-python-project-endifnpx skills add leynier/python-template --skill if-deploy_target-none-deploy-python-project-endifgit clone --depth 1 https://github.com/leynier/python-templateWhat 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 | $0.00050 | $0.00329 |
| Opus 5 | $0.00025 | $0.00164 |
| Sonnet 5 | $0.00010 | $0.00066 |
| Haiku 4.5 | $0.00005 | $0.00033 |
Grade A, and why
deploy-python-project 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.
What it actually says
Deploy Python Project
Read .copier-answers.yml and deploy/README.md first; they identify the target, commands, environment variables, and any generated IaC.
Workflow
- Run the full project quality gates from
project-workflow. - Build the generated Dockerfile locally. Start the image with explicit environment variables and verify its documented health route.
- Validate target configuration as structured JSON, TOML, YAML, Python, or HCL. Never infer that a successful parse proves cloud readiness.
- For Pulumi, run a preview before update. For Terraform, run format, init without changing remote state where possible, validate, and plan before apply.
- Confirm account, region, project, service name, expected cost boundary, secrets source, and rollback strategy before creating or changing remote resources.
- Deploy with the command documented in
deploy/README.md, then verify the remote health route and one representative request. - Report the deployed revision, endpoint, verification evidence, and any manual DNS or secret-management step.
Safety
- Do not deploy, apply IaC, delete resources, or expose a public endpoint without explicit authorization.
- Do not embed provider credentials in images, configuration, logs, or Git.
- Keep the Docker path usable even when the selected managed platform provides a native adapter.
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.
- 2d ago First seen · 25 lines · 50 tokens per session scan A 25fc7d1c395f
deploy-python-project is a skill published in the GitHub repository leynier/python-template (37 stars, last pushed 4d ago), licensed MIT. It adds 50 tokens to every session and 329 once invoked, about $0.0003 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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