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概要と使いどころ

End-to-end Solana development playbook (Jan 2026). Prefer Solana Foundation framework-kit (@solana/client + @solana/react-hooks) for React/Next.js UI. Prefer @solana/kit for all new client/RPC/transaction code. When legacy dependencies require web3.js, isolate it behind @solana/web3-compat (or @solana/web3.js as a true legacy fallback). Covers wallet-standard-first connection (incl. ConnectorKit), Anchor/Pinocchio programs, Codama-based client generation, LiteSVM/Mollusk/Surfpool testing, and security checklists.

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。

heyAyushh/stacc32026年9月21日 更新

council

無料

Multi-agent exploration and task delegation for complex areas of interest. Use when you need to deeply explore a codebase area, gather information from multiple perspectives, or delegate parallel research tasks for comprehensive analysis.

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。

heyAyushh/stacc32026年9月21日 更新

deslop

無料

Remove AI-generated code slop and improve code quality. Use when you need to clean up AI-written code, remove unnecessary defensive patterns, eliminate inconsistent comments, or align code style with the rest of the codebase.

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。

heyAyushh/stacc32026年9月21日 更新

init

無料

Initialize AGENTS.md documentation for a codebase. Use when setting up a new repository for AI coding assistants, creating project documentation for Claude Code or Cursor, or improving existing AGENTS.md files.

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。

heyAyushh/stacc32026年9月21日 更新

fix-pr

無料

Read all suggested PR changes and apply them directly to the codebase. Use when you have PR review comments to address, suggested changes to implement, or feedback to incorporate into your code.

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。

heyAyushh/stacc32026年9月21日 更新

bun

無料

Bun runtime and modern JavaScript backend practices, including Bun-native tooling (bun run/test/build) and PostgreSQL usage guidance. Use when building or reviewing Bun-based services, APIs, scripts, or when Bun-specific workflow questions arise.

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。

heyAyushh/stacc32026年9月21日 更新

Write or revise AI-learning-notes article pages in "寫文章模式" when the user asks for articles, technical articles, blog posts, bilingual versions, article formatting consistency, shared article-base alignment, responsive layout, summary/TOC decisions, contrast, or publishing-flow compatibility.

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。

eaglhuang/3klife32026年10月14日 更新

Generate realistic, correctly-linked Frappe/ERPNext test records for any DocType using the `bench faker` CLI, then roll them back when done. Use when a test, demo, or local repro needs seed data and the site is missing it — e.g. "I need some Sales Orders", "seed data so I can test this API", "create test Employees in Chennai", or "populate the database to test this endpoint".

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。

wreckage0907/frappe_faker32026年9月21日 更新

socratic

無料

Break a stuck or complex problem into the smallest sub-question that, if answered, unlocks the next step — then answer it and repeat until the path forward is clear. Load when a problem feels genuinely stuck, when reasoning keeps circling, or when deep-thinking diagnoses a Socratic frame. Also triggers on "I keep going in circles", "what is the real question here", "help me reason through this step by step", "unstick my thinking", "recursive questioning", "what is the root question". Based on the recursive Socratic questioning method (EMNLP 2023) which outperforms CoT and Tree-of-Thought on complex reasoning tasks.

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。

dvy1987/agent-loom32026年8月8日 更新

Think through the consequences of consequences — not just what happens immediately, but what happens next, and next after that, across time. Load when a decision looks obviously good or obviously bad on initial read, when the user is optimising for a short-term outcome that might create a long-term problem, when unintended consequences are a concern, or when deep-thinking diagnoses a second-order frame. Triggers on "what are the downstream effects", "what happens after that", "unintended consequences", "think ahead on this", "long-term vs short-term", or "what comes after that". Based on Howard Marks second-level thinking and Farnam Street mental models. Most powerful for decisions with delayed consequences or systemic effects.

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。

dvy1987/agent-loom32026年8月8日 更新

Run a pre-mortem — imagine the project has already failed one year from now and work backward to find the root causes before they happen. Load when the user asks for a pre-mortem, wants to imagine failure before committing, asks "what could go wrong before we start", "assume this fails — why", "risk analysis before launch", "what kills this project", "what could go wrong", or when deep-thinking diagnoses a pre-mortem frame. Based on Gary Klein's prospective hindsight method, which surfaces failure causes more effectively than forward risk analysis. Most useful right before a major commitment.

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。

dvy1987/agent-loom32026年8月8日 更新

ooda

無料

Apply Boyd's OODA loop to navigate fast-moving, uncertain, or competitive situations — Observe what is actually happening, Orient through mental models and context, Decide on the clearest path, Act quickly, then loop again. Load when the situation is changing faster than the current plan, when a competitive response is needed, when the user is stuck in analysis paralysis in a dynamic environment, when shipping under uncertainty, or when deep-thinking diagnoses a fast-moving / competitive frame. Triggers on "what should we do right now", "the situation is changing", "how do we respond to this", "competitive response", "we need to move fast", or "we're stuck deciding". Based on John Boyd's OODA loop — Observe, Orient, Decide, Act — adapted for product and business contexts (OODA Canvas 2026).

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。

dvy1987/agent-loom32026年8月8日 更新

Capture actionable learnings that emerge during conversation — when the agent or user discovers that a skill, a set of skills, or a process needs to be updated based on what's happening in the current chat. Sub-skill of the learn-from orchestrator. Load when the user says "we should update the skill for this", "this should be a skill rule", "add this as a gotcha", "the skill should know about this", "update the process for this", "remember this for next time", "this is important for the skill". Also triggers when the agent notices a skill's guidance was wrong or incomplete, a process step failed or was unnecessary, a new pattern emerged, a guardrail was missing, a workaround became a pattern, or a debugging session reveals a gap.

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。

dvy1987/agent-loom32026年8月8日 更新

Measure, profile, and fix performance bottlenecks — Core Web Vitals, backend latency, bundle size, and database queries. Load when performance requirements exist, users report slowness, profiling reveals bottlenecks, or the user asks to optimize load time, LCP, INP, CLS, or response time. Not for premature optimization without evidence. Pairs with browser-testing-with-devtools and ci-cd-and-automation for regression guards.

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。

dvy1987/agent-loom32026年8月8日 更新

Bootstrap full agent infrastructure for an existing, already-coded project without modifying a single line of source code. Surveys the repo, infers conventions from manifests, README, git history, and source samples, then generates the missing AGENTS.md, docs/architecture.md, docs/product-soul.md, ADR backfill, and seeded docs/memory/ files. Asks the user only about gaps the repo cannot reveal. Load when the user asks to "retroactive project setup", "backfill agent infrastructure", "bootstrap agents for this existing repo", "onboard agents to a legacy codebase", "set up agents without touching code", or "fill in missing agent context for this project".

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。

dvy1987/agent-loom32026年8月8日 更新

Generate a tailored AGENTS.md for any new project by interviewing the user about their skill gaps, project goals, and tech context. Load when the user asks to set up a project, initialize agents, create an AGENTS.md, bootstrap a repo, onboard agents to a codebase, or says "set up this project for agents". Also triggers on "write an AGENTS.md for this project", "configure agents for my repo", "project bootstrap", "agent onboarding", or when the user starts a new project and needs agent-ready configuration. Re-run when new context arrives (PRD written, stack changes, team changes) to update the AGENTS.md.

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。

dvy1987/agent-loom32026年8月8日 更新

Critically audit agent skills and remove content that is outdated, disproven, model-specific, or based on poorly cited sources. Load when improve-skills runs its per-skill cycle, when the user asks to prune skills, remove outdated techniques, check if skills are still valid, verify citations in skills, audit skill sources, or update skills for a new model release. Also triggers on "are these skills still valid", "check for obsolete techniques", "verify skill citations", or "update skills for GPT-5/Claude 4/Gemini 2". Runs before split-skill and compress-skill — removing bad content first means the remaining content is worth preserving.

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。

dvy1987/agent-loom32026年8月8日 更新

Surface every assumption embedded in a plan, strategy, or document, assess how critical and how validated each one is, and identify which ones to test first. Load when the user asks to map assumptions, surface hidden beliefs, find what must be true for this to work, run an assumption audit, or when deep-thinking diagnoses an assumption frame. Also triggers on "what are we assuming", "what must be true for this to work", or "find the untested beliefs". Based on David Bland and Alex Osterwalder's assumption mapping method from Testing Business Ideas.

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。

dvy1987/agent-loom32026年8月8日 更新

Strip a problem to its irreducible fundamental truths and rebuild the solution from the ground up — free from analogy, convention, and inherited assumptions. Load when the user feels constrained by how something has always been done, when existing solutions feel expensive or inefficient for no good reason, when the user asks to think from first principles, challenge the fundamentals, or rebuild this from scratch. Also triggers on "why does it have to work this way", "what are the actual constraints here", "ignore what everyone else does", or when deep-thinking diagnoses a convention-break frame. Based on Aristotle's first principles method, popularised by Musk and Feynman. Produces genuinely novel solutions by eliminating convention.

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。

dvy1987/agent-loom32026年8月8日 更新

Orchestrator for the experimentation skill suite — turn assumptions and product questions into rigorous, well-instrumented experiments and decision-grade readouts. Routes through backlog → spec → runbook → readout based on user need and existing artefacts. Platform-agnostic with PostHog as the primary binding. Load when the user asks to design an experiment, A/B test something, set up an experiment, run a holdout, test a hypothesis, decide what to test next, read out experiment results, analyse a test, or says "should we A/B test this", "experiment on the landing page", "is this lift real", "ship or kill this test", "what should we test next", "build an experiment backlog", "test the pricing page", "validate this with an experiment".

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。

dvy1987/agent-loom32026年8月8日 更新

Select alternative execution paths when a plan step fails — branch on outcomes instead of blind retry. Load when a structured plan step fails, an unexpected observation arrives, or the user asks what to try next after an error. Also triggers on "try another approach", "route around this failure", "replan on failure", "if X fails try Y", or outcome-based branching during multi-step work. Pairs with structured-planning and debug-and-fix. Does not replace root-cause debugging — adds plan-level path selection.

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。

dvy1987/agent-loom32026年8月8日 更新

fermi

無料

Decompose an unknown quantity into 3-5 estimable factors and produce a defensible order-of-magnitude answer without needing precise data. Load when the user needs to size something without data — market size, resource requirements, effort estimates, user numbers, costs — or when a decision is blocked by "we don't know the numbers". Also triggers on "ballpark this", "rough estimate", "how big is this market", "how long would this take", "how many users", or when deep-thinking diagnoses a sizing/estimation frame. The goal is not precision — it is a defensible answer that enables a decision to be made. Based on Enrico Fermi's estimation method.

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。

dvy1987/agent-loom32026年8月8日 更新

Map symbol dependencies, callers, and blast radius before editing code. Load when the user asks what depends on a symbol, what breaks if they change something, blast radius of a change, reverse dependencies, or which tests cover a function. Also triggers on "who calls this", "impact of changing", "dependency map", "what uses this", "find callers", or before any non-trivial edit when safe-change is not yet active. Pairs with codebase-understanding for broad architecture; this skill is symbol-scoped and edit-gated.

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。

dvy1987/agent-loom32026年8月8日 更新

Review a built frontend against its chosen direction, catch drift back to generic AI defaults, enforce state coverage, ethical patterns, UX heuristics, and polish, and check contrast with APCA (not the legacy WCAG ratio). Produces specific, prioritized fixes — never vibes-based feedback. Works with pasted screenshots or Playwright MCP automated capture. Load when the user asks to review a UI, audit a design, check if a frontend looks generic or vibecoded, evaluate visual quality or polish, says "review this UI", "is this design good", "audit my frontend", "does this feel like [product]", "design QA", or when frontend-design routes here. Sub-skill of frontend-design.

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。

dvy1987/agent-loom32026年8月8日 更新