LLM Mart Basic
@llm-mart · Joined Jun 2026
当 FDE 需要对工作流节点做 AI 分类判定时用这个 Skill—— 不是"它是干什么的",是"什么时候用"。 写错 description = Skill 永远不会被触发。
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Build and configure Cecil static sites, with focused guidance for content, templates, and site generation.
Deliver a change through an approved design contract, sequential implementation, independent review and exact-HEAD release. Use for any Bounded or Architectural change — including a small, one-line behavioral fix, which is the canonical Bounded case — so it gets design approval a
**ANALYSIS SKILL** — Analyze any repository and generate AI-ready configuration — a canonical AGENTS.md, thin per-tool pointer files, skills, CI workflows, issue templates. WHEN: "make this repo ai-ready", "set up AI config", "add copilot instructions", "prepare this repo for AI
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to"
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to"
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystem
Create, track and update team goals in Hivemind via the `hivemind` CLI. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystem
Validates and bootstraps Amazon Bedrock AgentCore observability so customers can trace
Comprehensive operational review procedures for Amazon Bedrock
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/generate-idl-client
Generate idl client
Generate a typed client from an Anchor or Shank IDL (Codama or Anchor TS)
/migrate-web3
Migrate web3
Migrate TypeScript from @solana/web3.js 1.x to @solana/kit
/plan-feature
Plan feature
Plan a Solana feature before coding: accounts, PDAs, instructions, risks, tests
/product-review
Product review
First-time-user product review: scorecard and fix roadmap; --harsh for a roast
/profile-cu
Profile cu
Measure compute units per instruction and flag the expensive ones
/quick-commit
Quick commit
Format, lint and commit with a conventional message on a kit-named branch
/resync
Resync
Resync external skill submodules to latest upstream versions
/scaffold
Scaffold
Scaffold a Solana project (Anchor, fullstack, frontend, Pinocchio) with the kit
/setup-ci-cd
Setup ci cd
Set up GitHub Actions CI for Solana programs: lint, build, test, audit
/setup-mcp
Setup mcp
Configure MCP server API keys in .env and add the optional MCP servers
/test-and-fix
Test and fix
Run tests, auto-fix fmt and lint, and fix failures until green or stuck
/test-dotnet
Test dotnet
Run C# tests: Unity Test Framework in batchmode, or dotnet test
/test-rust
Test rust
Run Rust tests for programs (LiteSVM, Mollusk, Surfpool, Trident) and backends
/test-ts
Test ts
Run TypeScript tests for programs (Anchor TS, Kit) and dApp frontends
/update
Update
Update solana-ai-kit to latest version from upstream
/write-docs
Write docs
Write docs for a Solana program, SDK or component from its code and IDL
/a
A
Allow all file creation (short for /ar:allow)
/afa
Afa
Set AutoFile policy to allow-all mode (full file creation permissions)
/afj
Afj
Set AutoFile policy to justify-create mode (require justification for new files)
/afs
Afs
Set AutoFile policy to strict-search mode (only modify existing files)
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