OpenEnv is a framework for creating, deploying, and using isolated execution environments through simple APIs modeled on Gymnasium. It is intended for researchers and developers training agents with reinforcement learning, as well as creators who need secure environments that can be deployed and accessed through familiar protocols. The catalogue add-ons provide agent integrations and workflows for using OpenEnv.
Borrowing it
Nothing to install: this file belongs to huggingface/OpenEnv. 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/huggingface/OpenEnv/main/.claude/skills/sprint/SKILL.mdgit clone --depth 1 https://github.com/huggingface/OpenEnvWrote 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/huggingface/openenv/sprint)<a href="https://agentmods.dev/skills/huggingface/openenv/sprint"><img src="https://agentmods.dev/badge/skills/huggingface/openenv/sprint/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/huggingface/openenv/sprint"><img src="https://agentmods.dev/badge/skills/huggingface/openenv/sprint.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 167 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00040 | $0.01725 |
| Opus 5.5 | $0.00016 | $0.00690 |
| Sonnet 5.5 | $0.00008 | $0.00345 |
| Haiku 4.5 | $0.00004 | $0.00172 |
Grade A, and why
sprint scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/sprint
Work on multiple GitHub issues in parallel. Each issue gets its own worktree with TDD enforcement. A lead agent coordinates, and stacked PRs are created when all work is done.
EXECUTE THESE STEPS NOW
When this skill is invoked, you MUST execute these steps immediately.
Step 0: Check Agent Teams Support
Check if Agent Teams are available:
echo "${CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS:-not_set}"
If the value is not_set or empty, fall back to setup-only mode:
- Parse the comma-separated issue numbers
- Fetch requirements for all issues (parallel issue-worker agents)
- Create worktrees and activate TDD for each
- Report the list of prepared worktrees and tell the user:
"Agent Teams not enabled. Worktrees are prepared with TDD active.
cd into each worktree and run
/write-teststo begin the TDD cycle, or setCLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1and re-run/sprint." - Do NOT invoke
/work-on-issue— it would create duplicate worktrees. The worktrees and TDD markers are already set up.
Step 1: Parse Issue Numbers
Extract comma-separated issue numbers from $ARGUMENTS:
- Remove
#prefixes, spaces, and other punctuation - Example:
67,68,69,70or#67 #68 #69 - Store as a list:
ISSUES=(67 68 69 70)
Step 2: Fetch Requirements (Parallel)
Spawn one issue-worker agent per issue, all in a single message so they run in parallel:
Task tool (ALL in one message):
For issue 67:
subagent_type: issue-worker
description: "issue-worker #67"
prompt: "Read GitHub issue #67 and extract:
1. Goal
2. Acceptance criteria
3. Edge cases and constraints
4. Files likely to be touched"
For issue 68:
subagent_type: issue-worker
description: "issue-worker #68"
prompt: "Read GitHub issue #68 and extract: ..."
(etc.)
Wait for all agents to return. Collect requirements for each issue.
Step 3: Create Worktrees and Activate TDD
For each issue, create a worktree and activate TDD:
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.
- 1mo ago First seen · 226 lines · 40 tokens per session scan A fbd155a5a396
sprint is a skill published in the GitHub repository huggingface/OpenEnv (2,739 stars, last pushed 8d ago), licensed BSD-3-Clause. It adds 40 tokens to every session and 1,725 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
antfu-issue-triage
Triage open issues and PRs of the current GitHub repo - find already-fixed, duplicate, and spam items, suggest labels, gauge demand from reactions and comments, then present a table of proposed actions and comments for confirmation before touching anything. Use when asked to triage, organize, clean up, or groom issues…
mcore-split-pr
Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.
engineer-bot-ops
A workflow for carrying an engineering task from scope through implementation and reviewable delivery. It works with a repository's branch, existing changes, rules, checks, and permissions while separating completed, unverified, and next-step work.
shiplog
Recap of everything shipped since the last run - cross-repo PRs, security fixes, star deltas, and X traction, synthesized into a digest article and a ready-to-post shiplog in your voice.
connect
Choose which wiki this session uses, the team project's pages on the Nimbalyst server or the project's local wiki of files, and connect a repository to its team project. Use at the start of a task before any wiki tool, when a wiki tool returns reponotbound, ambiguousproject, pinmismatch, projectnotaccessible…
llxprt-issue-workflow
Use this skill when asked to address, fix, or work on a GitHub issue in the llxprt-code repository. Covers the complete issue lifecycle - branch setup, gh CLI usage, test-first planning, subagent delegation and review loops, the full verification cycle (including the zai-glm-flash smoke test), open code review (ocr)…