Azure Functions
davila7/claude-code-templates
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns.
Guide for adding a new reward function to AReaL. An agent skill from areal-project/AReaL.
$ npx skills add areal-project/AReaL --skill add-reward -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install areal-project/AReaL add-reward --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/areal-project/AReaL.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/add-reward .claude/skills/add-reward && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "add-reward" agent skill from https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-reward into .claude/skills/add-reward/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-reward", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-rewardType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add areal-project/AReaL --skill add-reward -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install areal-project/AReaL add-reward --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/areal-project/AReaL.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/add-reward .agents/skills/add-reward && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "add-reward" agent skill from https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-reward into .agents/skills/add-reward/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-reward", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add areal-project/AReaL --skill add-reward -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install areal-project/AReaL add-reward --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/areal-project/AReaL.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/add-reward .cursor/skills/add-reward && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "add-reward" agent skill from https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-reward into .cursor/skills/add-reward/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-reward", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/areal-project/AReaL.git --path .agents/skills/add-reward--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add areal-project/AReaL --skill add-reward -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install areal-project/AReaL add-reward --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/areal-project/AReaL.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/add-reward .gemini/skills/add-reward && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "add-reward" agent skill from https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-reward into .gemini/skills/add-reward/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-reward", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install areal-project/AReaL add-rewardInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add areal-project/AReaL --skill add-reward -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/areal-project/AReaL.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/add-reward .github/skills/add-reward && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "add-reward" agent skill from https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-reward into .github/skills/add-reward/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-reward", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add areal-project/AReaL --skill add-reward -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install areal-project/AReaL add-reward --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/areal-project/AReaL.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/add-reward .opencode/skills/add-reward && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "add-reward" agent skill from https://github.com/areal-project/AReaL/tree/main/.agents/skills/add-reward into .opencode/skills/add-reward/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-reward", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
add-rewardGuide for adding a new reward function to AReaL. An agent skill from areal-project/AReaL.
Add Reward is an agent skill from areal-project/AReaL. Guide for adding a new reward function to AReaL. Use when user wants to create a reward function.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: The RL Bridge for LLM-based Agent Applications. Made Simple & Flexible. The licence is Apache-2.0.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 298412a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Add Reward loads about 1.2k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 207 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from areal-project/AReaL at commit 298412a, republished under its Apache-2.0 licence (© areal-project). 207 words, ~1,237 tokens.
.claude/skills/add-reward/SKILL.md (or your agent's skills folder).Add a new reward function to AReaL.
This skill is triggered when:
Create areal/reward/<name>.py:
from typing import Any
from areal.utils import logging
logger = logging.getLogger("MyReward")
def <name>_reward_fn(
prompt: str,
completions: str,
prompt_ids,
completion_ids,
answer: str | None = None,
**kwargs: Any,
) -> float:
"""Compute reward for a single completion.
Args:
prompt: Prompt string
completions: Completion string (model output)
prompt_ids: Tokenized prompt IDs
completion_ids: Tokenized completion IDs
answer: Ground truth answer from dataset (optional)
**kwargs: Additional data from dataset
Returns:
Reward value (float), typically 0.0 or 1.0
"""
try:
# Extract answer from completion
extracted = _extract_answer(completions)
# Compare with ground truth
if answer is not None and extracted == str(answer):
return 1.0
return 0.0
except Exception:
logger.warning("Exception in reward computation", exc_info=True)
return 0.0
def _extract_answer(completion: str) -> str:
"""Extract the answer from a completion string.
Implement your extraction logic here.
"""
# Example: Extract content from \boxed{}
import re
match = re.search(r"\\boxed\{([^}]+)\}", completion)
if match:
return match.group(1).strip()
return completion.strip()Update areal/reward/__init__.py:
# Add to VALID_REWARD_FN
VALID_REWARD_FN = [
# ... existing reward functions
"<name>",
]
# Add to get_reward_fn function
def get_reward_fn(name: str, **kwargs):
# ... existing code
elif name == "<name>":
from areal.reward.<name> import <name>_reward_fn
return <name>_reward_fnIf your reward function uses blocking operations (e.g., API calls, model inference), the
workflow will wrap it with AsyncRewardWrapper:
# In your workflow
from areal.reward import AsyncRewardWrapper
self.reward_fn = AsyncRewardWrapper(reward_fn)
# Then call it asynchronously
rewards = await self.reward_fn(prompt, completions, **data)Create tests/test_<name>_reward.py:
import pytest
from areal.reward.<name> import <name>_reward_fn
def test_reward_correct_answer():
reward = <name>_reward_fn(
prompt="What is 2+2?",
completions="The answer is \\boxed{4}",
prompt_ids=None,
completion_ids=None,
answer="4",
)
assert reward == 1.0
def test_reward_wrong_answer():
reward = <name>_reward_fn(
prompt="What is 2+2?",
completions="The answer is \\boxed{5}",
prompt_ids=None,
completion_ids=None,
answer="4",
)
assert reward == 0.0| Reward | File | Description |
|---|---|---|
| GSM8K | areal/reward/gsm8k.py | Math answer verification |
| Geometry3K | areal/reward/geometry3k.py | Geometry answer verification |
| CLEVR | areal/reward/clevr_count_70k.py | Counting verification |
| MathVerify | areal/reward/math_verify.py | General math verification |
All reward functions must follow this signature:
def reward_fn(
prompt: str, # Input prompt string
completions: str, # Model completion string
prompt_ids, # Tokenized prompt
completion_ids, # Tokenized completion
**kwargs: Any, # Additional data from dataset (e.g., answer)
) -> float: # Reward value (typically 0.0 or 1.0)Note: The reward function is called once per sample. Batching is handled by
AsyncRewardWrapper in the workflow.
AsyncRewardWrapper if neededareal.utils.logging, not printAsyncRewardWrapper© areal-project, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/add-reward of areal-project/AReaL.
Open the folder on GitHubat commit 298412a
Add Reward next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Add Reward this skillareal-project/AReaL | 5.8k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Azure Functionsdavila7/claude-code-templates | 33k | 2 repos | ~344 | Automated safety check: Pass | MIT | |
| Recognition Rewardssickn33/agentic-awesome-skills | 47k | 1 repos | ~3.4k | Automated safety check: Pass | MIT | |
| Neon Functionssickn33/agentic-awesome-skills | 47k | 1 repos | ~8.6k | Automated safety check: Notes | Apache-2.0 | |
| GCP Cloud Functionssickn33/agentic-awesome-skills | 47k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Securing Serverless Functionsmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~3.1k | Automated safety check: Pass | Apache-2.0 |
davila7/claude-code-templates
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns.
sickn33/agentic-awesome-skills
Recognition register: employee, reward type, category, visibility, message and points awarded.
sickn33/agentic-awesome-skills
Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASEURL injected automatically and compute that runs next to your data.
sickn33/agentic-awesome-skills
Deploy serverless functions on Google Cloud Functions. An agent skill from sickn33/agentic-awesome-skills.
mukul975/Anthropic-Cybersecurity-Skills
Hardens serverless compute platforms (AWS Lambda, Azure Functions, Google Cloud Functions): least-privilege IAM roles, dependency vulnerability scanning, secrets management integration, input…
mukul975/Anthropic-Cybersecurity-Skills
Performing security reviews of serverless functions across AWS Lambda, Azure Functions, and GCP Cloud Functions to identify overly permissive execution roles, insecure environment variables…
areal-project/AReaL
Guide for adding a new model to the Archon engine. An agent skill from areal-project/AReaL.
areal-project/AReaL
Guide for adding a new dataset loader to AReaL. An agent skill from areal-project/AReaL.
areal-project/AReaL
Guide for adding unit tests to AReaL. An agent skill from areal-project/AReaL.
areal-project/AReaL
Guide for adding a new RolloutWorkflow to AReaL. An agent skill from areal-project/AReaL.
areal-project/AReaL
Guide for debugging distributed training issues in AReaL. An agent skill from areal-project/AReaL.
areal-project/AReaL
Read-only pull request review workflow with risk analysis, targeted checklists, and Codex subagent consultation.
Guide for adding a new reward function to AReaL. An agent skill from areal-project/AReaL. Add Reward is an agent skill from areal-project/AReaL. Guide for adding a new reward function to AReaL.
Add Reward fits situations like: user wants to create a reward function.
Run `npx skills add areal-project/AReaL --skill add-reward -a claude-code`. Or copy the skill folder (.agents/skills/add-reward in areal-project/AReaL) into .claude/skills/add-reward in your project. Claude Code loads it when a task matches its description.
Run `npx skills add areal-project/AReaL --skill add-reward -a codex`. Or copy the skill folder (.agents/skills/add-reward in areal-project/AReaL) into .agents/skills/add-reward in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add areal-project/AReaL --skill add-reward -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/add-reward, .gemini/skills/add-reward, .github/skills/add-reward and .opencode/skills/add-reward in your project.
SKILL.md names no scripts, command-line tools or credentials: Add Reward is instructions for the agent only. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Add Reward is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Add Reward: Azure Functions (davila7/claude-code-templates, 33k stars), Recognition Rewards (sickn33/agentic-awesome-skills, 47k stars), Neon Functions (sickn33/agentic-awesome-skills, 47k stars) and GCP Cloud Functions (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
areal-project (a GitHub organization) maintains it in areal-project/AReaL, which has 5,824 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 10, 2026.
Source: areal-project/AReaL on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.