FastVideo is a framework for training and running accelerated video-generation models, including real-time inference and post-training workflows. It is for researchers and developers building or deploying diffusion-based systems that generate video.
Borrowing it
Nothing to install: this file belongs to hao-ai-lab/FastVideo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hao-ai-lab/FastVideo/main/.agents/skills/env-var-conventions/SKILL.mdgit clone --depth 1 https://github.com/hao-ai-lab/FastVideoWrote 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/hao-ai-lab/fastvideo/env-var-conventions)<a href="https://agentmods.dev/skills/hao-ai-lab/fastvideo/env-var-conventions"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/env-var-conventions/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/hao-ai-lab/fastvideo/env-var-conventions"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/env-var-conventions.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00064 | $0.00865 |
| Opus 5.5 | $0.00026 | $0.00346 |
| Sonnet 5.5 | $0.00013 | $0.00173 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
env-var-conventions 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 29d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Environment Variable Conventions
Purpose
FastVideo registers its environment variables as typed fields in
fastvideo/envs.py. The policy that governs them is
docs/contributing/env_vars.md, and the contract test
fastvideo/tests/contract/test_env_policy.py enforces the policy in the unit
CI lane. This skill routes an environment-variable change through that policy.
The policy doc is the single source of the rules; read it instead of relying
on a summary here.
Prerequisites
- Read
docs/contributing/env_vars.mdin full. - Decide whether the setting belongs in an environment variable or an argument
(rule 5 in the policy doc). Settings that users change per deployment are
arguments; add them through
fastvideo/fastvideo_args.pyinstead.
Inputs
| Parameter | Required | Description |
|---|---|---|
change |
Yes | Add, read, rename, or remove a variable, or change the policy. |
variable |
Yes | The variable name, with the FASTVIDEO_ prefix. |
Steps
- Declare or edit the variable in
fastvideo/envs.py.- Pick the field type and category that the policy doc lists.
- Write a description that states what the variable does and its units.
- To rename, keep the old name in
deprecated_names. To remove, add the name toDEPRECATED_VARIABLES. Update the uses inexamples/,scripts/,docs/,apps/, and the tests.
- Read the variable with
envs.NAME.get()inside a function.- In tests, change the value with
envs.NAME.override(value), and a variable outside the registry withenvs.override_external(name, value); theenv_overridesfixture keeps either until the end of the test. - Name a variable that only tests read
FASTVIDEO_TEST_*. - Do not call
os.environ,os.getenv, ormonkeypatch.setenvfor a FastVideo variable. - To set a variable that another tool reads, call
envs.set_external,envs.setdefault_external, orenvs.unset_external.
- In tests, change the value with
- Regenerate the table in the policy doc.
- Run
python fastvideo/tests/contract/test_env_policy.py.
- Run
- Run the contract test.
- Run
pytest fastvideo/tests/contract/test_env_policy.py. - When the test reports a fixed known violation, delete or lower its entry
in
KNOWN_VIOLATIONS. Never add an entry toKNOWN_VIOLATIONS.
- Run
- When the policy itself changes, update the policy doc and the contract
test in the same pull request.
- The rules in
docs/contributing/env_vars.md, the checks and allowlist infastvideo/tests/contract/test_env_policy.py, and this skill must agree.
- The rules in
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.
- 29d ago Changed · +3 lines e3ceeb085cc8
- 1mo ago First seen · 77 lines · 64 tokens per session scan A bfbe0e1fd0b1
env-var-conventions is a skill published in the GitHub repository hao-ai-lab/FastVideo (4,758 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 865 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-30.
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