Repository
adithya-s-k/FineEnvs agent skills
- skills
- 8
- GitHub stars
- 456
GitHub description: “FineEnvs — RL Environments 101: building and scaling RL environments in the age of LLMs”
- Stars
- 456 (60 forks)
- Licence
- Apache-2.0
- Last push
- Oct 2026
- Created
- May 2026
- Homepage
- huggingface.co/FineEnvs
- agents
- grpo
- huggingface
- llm
- openenv
- reinforcement-learning
- rl-environments
- rlhf
- trl
Install all skills
npx skills add adithya-s-k/FineEnvsAdd --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).
Skills in adithya-s-k/FineEnvs, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Builds a Verifiers (PrimeIntellect) variant of an RL environment. | adithya-s-k/ | 456 | 1 repo | ~2.3k | Automated safety check: Pass | Apache-2.0 | today |
| 2 | Builds a NeMo Gym (NVIDIA) variant of an RL environment. An agent skill from adithya-s-k/FineEnvs. | adithya-s-k/ | 456 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | today |
| 3 | Builds an OpenEnv (Hugging Face) variant of an RL environment. | adithya-s-k/ | 456 | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | today |
| 4 | Builds an Open Reward Standard (ORS) variant of an RL environment using the official openreward Python package. | adithya-s-k/ | 456 | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | today |
| 5 | Turns a user's plain-English description of an RL training environment into runnable code across the four target frameworks — OpenEnv, OpenReward (ORS), Verifiers, and NeMo Gym. | adithya-s-k/ | 456 | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | today |
| 6 | Configure article metadata via MDX frontmatter. An agent skill from adithya-s-k/FineEnvs. | adithya-s-k/ | 456 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | today |
| 7 | Create self-contained D3 HTML embed charts for the research article template. | adithya-s-k/ | 456 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | today |
| 8 | Deploy the article to a Hugging Face Space. An agent skill from adithya-s-k/FineEnvs. | adithya-s-k/ | 456 | — | ~864 | Automated safety check: Pass | Apache-2.0 | today |
Questions, answered from the data.
What is the best skill in adithya-s-k/FineEnvs?
Generate Verifiers Env from adithya-s-k/FineEnvs ranks first of the 8 skills in adithya-s-k/FineEnvs listed here, with the highest score: its repository has 456 GitHub stars, 1 other GitHub owner carry a copy, its SKILL.md loads about 2.3k tokens and it passes the automated safety check with no findings. Next come Generate Nemo Gym Env and Generate Openenv Env.
Are the skills in adithya-s-k/FineEnvs official?
None yet. All 8 skills in adithya-s-k/FineEnvs listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How do I install all skills from adithya-s-k/FineEnvs?
Run npx skills add adithya-s-k/FineEnvs in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.