Link List

Uni­ver­sal Mark­down Proces­sor com­pat­i­ble with Com­mon­Mark, GFM, Mul­ti­Mark­down, Kram­down, mmark, and more — Home · ApexMarkdown/​apex Wiki

Claude Code’s out­put styles con­trol Claude’s role, tone, and response for­mat for soft­ware engi­neer­ing tasks. The doc­u­men­ta­tion explains four built-in styles — Proac­tive, Con­cise, Explana­to­ry, and Learn­ing — and how to con­fig­ure them via ter­mi­nal, VS Code exten­sion, or desk­top app. Users can also cre­ate cus­tom out­put styles using Mark­down files with front­mat­ter and instruc­tions.

Lar­avel Boost is a Lar­avel 13.x devel­op­ment tool that enhances AI-assist­ed cod­ing by pro­vid­ing guide­lines, agent skills, and a doc­u­men­ta­tion API with over 17,000 pieces of Lar­avel-spe­cif­ic infor­ma­tion. It inte­grates with AI agents like Claude Code and Cur­sor to help write high-qual­i­ty Lar­avel appli­ca­tions fol­low­ing best prac­tices. Instal­la­tion is done via Com­pos­er with the boost:install com­mand.

GitHub’s dsh-plu­g­in top­ic page dis­plays 11,124 pub­lic repos­i­to­ries tagged with dsh-plu­g­in, sortable by lan­guage and pop­u­lar­i­ty. Fea­tured projects include DeepSeek Har­ness plu­g­ins, AI agent frame­works, design tools, and devel­op­er util­i­ties, most­ly writ­ten in Type­Script and JavaScript. The page allows fil­ter­ing and sort­ing by stars, forks, and update fre­quen­cy.

DeepSeek Har­ness is a devel­op­er pre­view plat­form for build­ing AI agents with a mod­u­lar plu­g­in archi­tec­ture. Every capa­bil­i­ty — mod­els, tools, skills, stor­age, and UI — is a swap­pable plu­g­in built on the Cordis ker­nel. The frame­work offers mul­ti­ple run­time modes and full trace­abil­i­ty of agent actions through append-only ses­sion logs.

Design engi­neer at the inter­sec­tion of code, design and art. My own lit­tle space on the inter­net: side projects, writ­ing, pho­tog­ra­phy and post­cards.

Unsloth Desk­top is a free, open-source desk­top appli­ca­tion for run­ning and train­ing AI mod­els local­ly on macOS, Win­dows, and Lin­ux. It sup­ports LLMs, dif­fu­sion mod­els, and audio gen­er­a­tion with fea­tures includ­ing accu­rate tool calls, image/​video gen­er­a­tion, code exe­cu­tion, and remote deploy­ment via HTTPS.

Kil­ian Valkhof explains prac­ti­cal pro­gram­ming prin­ci­ples for self-taught front-end devel­op­ers, focus­ing on action­able rules-of-thumb like YAG­NI and DRY that improve dai­ly cod­ing deci­sions with­out requir­ing for­mal com­put­er sci­ence train­ing. Based on 20+ years of expe­ri­ence, the arti­cle trans­lates abstract con­cepts into use­ful habits for writ­ing bet­ter code incre­men­tal­ly.

Qwen3.6 deliv­ers sub­stan­tial upgrades in agen­tic cod­ing and think­ing preser­va­tion than pre­vi­ous Qwen mod­els.

Anthrop­ic’s blog post explain­ing how they sim­pli­fied con­text engi­neer­ing for Claude 5 mod­els by remov­ing over 80% of Claude Code’s sys­tem prompt. The arti­cle pro­vides best prac­tices for build­ing effec­tive gen­er­al prompts and guid­ance for advanced Claude mod­els, includ­ing lessons on reduc­ing unnec­es­sary con­straints and lever­ag­ing new tools like mem­o­ry and skills.

This repos­i­to­ry con­tains a sys­tem prompt frame­work (Guardrails Kit) designed to improve Claude Opus/​Sonnet’s code qual­i­ty by mak­ing explic­it the rea­son­ing rules that stronger mod­els apply implic­it­ly. It includes core guide­lines, plan­ning, cod­ing, debug­ging, and ver­i­fi­ca­tion pro­ce­dures, plus a migra­tion tool for retro­fitting exist­ing projects.

Thanks to Claude Code, Codex, and oth­er AI tools, any­one can now build func­tion­al apps. Which means every­one can build exact­ly the soft­ware they need.

Loop engi­neer­ing is a sys­tem design approach where devel­op­ers build auto­mat­ed recur­sive process­es to prompt AI cod­ing agents rather than man­u­al­ly prompt­ing them each turn. The sys­tem han­dles dis­cov­ery, task assign­ment, ver­i­fi­ca­tion, and iter­a­tion inde­pen­dent­ly, with five key com­po­nents: sched­uled automa­tions, iso­lat­ed work­trees, project knowl­edge doc­u­men­ta­tion, tool con­nec­tors, and sub-agents for check­ing work.

This arti­cle exam­ines ​“prompt debt,” the hid­den costs of rely­ing on hand-tuned nat­ur­al lan­guage prompts to spec­i­fy AI sys­tem behav­ior. It explains how ini­tial pro­to­typ­ing speed masks long-term prob­lems: slow­ing iter­a­tion cycles, team coor­di­na­tion chal­lenges, and mod­el lock-in that pre­vents upgrad­ing to bet­ter alter­na­tives. The author argues that nat­ur­al lan­guage was nev­er designed as an engi­neer­ing spec­i­fi­ca­tion lan­guage and treat­ing it as one fun­da­men­tal­ly lim­its scal­able AI appli­ca­tion devel­op­ment.

Short­cuts Play­ground is a free, open-source plu­g­in that con­verts plain Eng­lish descrip­tions into work­ing Apple Short­cuts files using AI agents like Claude. Users type a sen­tence and receive a ready-to-import .short­cut file with all actions, vari­ables, and log­ic auto­mat­i­cal­ly con­fig­ured, elim­i­nat­ing man­u­al drag-and-drop build­ing.

Short­cuts Play­ground is a free, open-source plu­g­in for Claude Code and Codex that gen­er­ates Apple Short­cuts using nat­ur­al lan­guage prompts. Users can request any short­cut and receive a ready-to-import file with­in min­utes. The Mac­Sto­ries Short­cuts Archive has been redesigned with new cat­e­gories and now includes 100 AI-gen­er­at­ed short­cuts ver­i­fied by the cre­ator.

Warp is an agen­tic devel­op­ment envi­ron­ment, born out of the ter­mi­nal. — warpdotdev/​warp

This GitHub page presents code­sight, a uni­ver­sal AI con­text gen­er­a­tor. It saves thou­sands of tokens for AI tools by build­ing a per­sis­tent knowl­edge base direct­ly from your code­base.

This GitHub repo describes Phan­tom, an AI co-work­er with its own com­put­er. It’s self-evolv­ing, has per­sis­tent mem­o­ry, builds tools, and runs on Slack.

This GitHub repo pro­vides best prac­tices for Claude Code. It details struc­tur­ing agents, com­mands, skills, and work­flows to opti­mize AI devel­op­ment.

This course helps web devel­op­ers inte­grate AI into web­sites and apps. It focus­es on plan­ning and respon­si­ble sys­tem design, not spe­cif­ic tools.

Gar­ry Tan’s gstack is a Claude Code set­up on GitHub. It uses 23 AI agents automat­ing roles from CEO to QA for rapid, high-vol­ume soft­ware devel­op­ment.

This page details 15 hid­den and under-uti­lized fea­tures for Claude Code, shared by its cre­ator Boris Cherny. Tips cov­er mobile app use, ses­sion trans­fer, and task automa­tion.

Anthrop­ic improved Claude’s autonomous cod­ing for com­plex app devel­op­ment. A mul­ti-agent sys­tem (gen­er­a­tor, eval­u­a­tor, plan­ner) tack­les long-run­ning task issues like con­text and self-eval­u­a­tion.

Overview of Frame­work v2, detail­ing its UI util­i­ties, com­po­nents, and guides. It cov­ers lay­out, styling, respon­sive design, and upgrade infor­ma­tion.

Most teams have repet­i­tive, high-vol­ume tasks that eat up their week: migrat­ing com­po­nents, gen­er­at­ing tests, audit­ing con­tent. Night­shift is a batch…

Simon Willison’s fire­side chat cov­ers agen­tic engi­neer­ing. He dis­cuss­es AI adop­tion, trust­ing AI out­put, and how cod­ing agents make test-dri­ven devel­op­ment ​“effec­tive­ly free.”

A Claude Code cheat sheet detail­ing key­board short­cuts, slash com­mands, MCP serv­er man­age­ment, mem­o­ry, and work­flows. Essen­tial for effi­cient use.

Neil Kakkar shares how Claude Code boosts his pro­duc­tiv­i­ty. He auto­mates tasks, speeds work­flows, and del­e­gates to AI agents, becom­ing a ​“man­ag­er of agents.”

AI ​“vibe cod­ing” does­n’t work with vague Eng­lish spec­i­fi­ca­tions. Mas­ter­ing soft­ware com­plex­i­ty requires abstrac­tion, not just AI, which is what cod­ing is.