Verified Spec-Driven Development (VSDD) is a unified software engineering methodology that fuses three proven paradigms into a single AI-orchestrated pipeline:
| name | codex-review |
|---|---|
| description | Send the current plan to OpenAI Codex CLI for iterative review. Claude and Codex go back-and-forth until Codex approves the plan. |
| user_invocable | true |
Send the current implementation plan to OpenAI Codex for review. Claude revises the plan based on Codex's feedback and re-submits until Codex approves. Max 5 rounds.
| ROLE="User Access Administrator" | |
| SUBSCRIPTION=$(az account show --query id -otsv) | |
| if [ ! -z "$RESOURCE_GROUP" ]; then | |
| SCOPE="/providers/Microsoft.Subscription/subscriptions/$SUBSCRIPTION/resourceGroups/$RESOURCE_GROUP" # Group-scoped | |
| echo "Scope (Group): $SCOPE" | |
| else | |
| SCOPE="/providers/Microsoft.Subscription/subscriptions/$SUBSCRIPTION" # Subscription-scoped | |
| echo "Scope (Subscription): $SCOPE" |
| /* | |
| STRINGS | |
| */ | |
| Assert.Equal(expectedString, actualString); | |
| Assert.StartsWith(expectedString, stringToCheck); | |
| Assert.EndsWith(expectedString, stringToCheck); | |
| // Some can also take optional params | |
| Assert.Equal(expectedString, actualString, ignoreCase: true); | |
| Assert.StartsWith(expectedString, stringToCheck, StringComparison.OrdinalIgnoreCase); |
| import sys | |
| import logging | |
| from typing import Optional, Dict | |
| from colorama import Fore, Back, Style | |
| class ColoredFormatter(logging.Formatter): | |
| """Colored log formatter.""" |
| #!pip install html5lib #install html5lib, only needs to be run once | |
| import pandas as pd | |
| import numpy as np | |
| df=pd.read_html('https://proxy.mentoracademy.org/getContentFromUrl/?userid=brooks&url=https://en.wikipedia.org/wiki/List_of_natural_satellites', header=0) | |
| moons=df[4][1:] #drop prehistoric moon sighting | |
| moons=moons['Discovery year'] #we are only interested in the year discovered | |
| moons=moons.apply(lambda x: x.split('/')[0]).astype(int) #clean dataframe to just years as ints | |
| pre_2000=len(moons[moons<2000]) #select only that data from moons which is less than 2000 | |
| post_2000=len(moons[moons>=2000]) #select only that data from moons which is greater than or equal to 2000 |
FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.
| const I = x => x | |
| const K = x => y => x | |
| const A = f => x => f (x) | |
| const T = x => f => f (x) | |
| const W = f => x => f (x) (x) | |
| const C = f => y => x => f (x) (y) | |
| const B = f => g => x => f (g (x)) | |
| const S = f => g => x => f (x) (g (x)) | |
| const S_ = f => g => x => f (g (x)) (x) | |
| const S2 = f => g => h => x => f (g (x)) (h (x)) |
| function mapValues(obj, fn) { | |
| return Object.keys(obj).reduce((result, key) => { | |
| result[key] = fn(obj[key], key); | |
| return result; | |
| }, {}); | |
| } | |
| function pick(obj, fn) { | |
| return Object.keys(obj).reduce((result, key) => { | |
| if (fn(obj[key])) { |
