Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Transform brain dumps into polished blog posts in Nick Nisi's voice. Use when the user wants to write a blog post with scattered ideas, talking points, and conclusions that need organization into a cohesive narrative with Nick's conversational, authentic, and thoughtful tone.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Transform unstructured brain dumps into polished blog posts that sound like Nick Nisi.
Accept whatever the user provides:
Don't require organization. The mess is the input.
Load references/voice-tone.md to understand Nick's writing style.
Key characteristics:
Read references/story-circle.md to understand the narrative framework.
Determine if the content fits a story structure:
Not every post needs the full Story Circle, but look for narrative opportunities.
Structure the material into sections:
Common structures:
Choose the structure that fits the content.
Apply voice characteristics:
Opening:
Body:
Technical content:
Tone modulation:
Ending:
Check the post:
Show the post to the user for feedback and iterate.
"AI is going to replace developers."
I must have heard that phrase a hundred times in the last year.
I've been thinking a lot about how we use AI in our daily work.
Then something clicked.
I watched it use rg to search through codebases, just like I would.
I won't lie – joining Meta was intimidating.
I watched it use `rg` to search through codebases, just like I would.
It ran `npm test` to verify its changes weren't breaking anything.
You're not being replaced; you're being amplified.
references/voice-tone.md - Complete voice and tone guide. Read this first to capture Nick's style.references/story-circle.md - Story Circle narrative framework. Check if content fits a story structure.User provides brain dump:
thoughts on using cursor vs claude code
- cursor is in IDE, feels familiar
- but claude code is in terminal, my natural environment
- tried cursor first, felt weird leaving vim
- claude code met me where I was
- not about which is better, about workflow fit
- some devs love IDE integration
- I need terminal access
- conclusion: use what fits YOUR workflow
Process:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
日本語の概要は準備中です。原文の説明を表示しています。
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。