LLM Mart Basic
@llm-mart · Joined Jun 2026
Add, review, or fix JavaScript interop in Blazor components. USE FOR: calling JavaScript from Blazor, calling .NET from JavaScript, collocated .razor.js modules, IJSRuntime, IJSObjectReference lifecycle, DotNetObjectReference, ElementReference, timing rules for when JS is availab
Imperative guidance for the System.Text.Json APIs added in .NET 11: the built-in `JsonNamingPolicy.PascalCase` naming policy, and the strongly-typed `JsonSerializerOptions.GetTypeInfo<T>()` and `JsonSerializerOptions.TryGetTypeInfo<T>(out JsonTypeInfo<T>? info)` metadata accessor
Author and review GitHub Actions workflow YAML safely so syntactically-valid YAML can't ship a workflow that GitHub Actions refuses to run. USE FOR: editing, adding, or reviewing any file under .github/workflows/, writing run-name/name/if/env/run values that contain ${{ }} expres
Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.
Scaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, writing a skill description that the runtime will actually route to, or setting up skill directory structures. Handles frontmatter generation, section templates,
Scaffolds eval.yaml evaluation specs for agent skills in the dotnet/skills repository. Use when creating skill tests, writing evaluation stimuli, defining graders and rubrics, sizing an eval for statistical power, or setting up test fixture files. Handles the Vally eval.yaml sche
Diagnoses and fixes skills in the dotnet/skills repository that lose to their own baseline, fail to activate, time out, or return "no credible improvement". Use when an evaluation verdict is a regression or underpowered, when a skill regressed after a change, when /evaluate repor
Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
Audits .NET test mock usage by tracing each mock setup through the production code's execution path to find dead, unreachable, redundant, or replaceable mocks. Use when the user asks to audit mock usage, find unused or unnecessary mock setups, check if mocks are needed, reduce mo
Detects duplicate boilerplate, copy-paste tests, and structural maintainability issues across .NET test suites. Use when the user asks to reduce repetition, consolidate similar test methods, convert copy-paste tests to data-driven parameterized tests, suggest a better test struct
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.
Analyzes .NET code for performance bottlenecks, recommends concrete optimizations, and guides benchmarking. Scans for ~50 anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O. Use when reviewing .NET code performance, optimizing hot paths,
Agent for diagnosing and optimizing MSBuild build performance. Runs multi-step analysis: generates binlogs, analyzes timeline and bottlenecks, identifies expensive targets/tasks/analyzers, and suggests concrete optimizations. Invoke when builds are slow or when asked to optimize
Agent that reviews MSBuild project files for anti-patterns, modernization opportunities, and best practices violations. Scans .csproj, .vbproj, .fsproj, .props, .targets files and produces actionable improvement suggestions. Invoke when asked to review, audit, or improve MSBuild
Expert agent for MSBuild and .NET build troubleshooting, optimization, and project file quality. Routes to specialized agents for performance analysis and code review. Verifies MSBuild domain relevance before deep-diving. Specializes in build configuration, error diagnosis, binar
Expert agent for .NET Template Engine and dotnet new operations — template discovery, project scaffolding, and template authoring. Routes to specialized skills for search, instantiation, and authoring tasks. Verifies template-engine domain relevance before deep-diving.
Orchestrates .NET test framework and platform migrations: auto-detects the current framework and version, routes to the appropriate migration skill, and guides users through end-to-end upgrades. Use when asked to upgrade MSTest, migrate to xUnit v3, switch to Microsoft.Testing.Pl
Runs build/compile commands for any language and reports results. Use when: compiling code, running dotnet build, checking for compilation errors, verifying project builds successfully.
Fixes compilation errors in source or test files. Use when: resolving build errors, fixing CS/TS error codes, adding missing imports, correcting type mismatches, fixing compilation failures.
Internal implementation agent for the code-testing-agent skill. Orchestrates the Research-Plan-Implement pipeline after that public entry-point skill delegates a test-generation request. Do not route user prompts here directly.
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.
/document
Document
Record the present state by mode — decision (ADR, RFC, rule), code (spec, doc, guide, scenario), or research (a ready report or one external material); a gate picks the document type.
/init
Init
First-time Archcore setup — wire host configs, measure the authored context, compose the full first-day seed in one preview, and create it on one confirm; import converts CLAUDE.md, AGENTS.md, rule files, ADRs, and docs into native documents; refresh adds new facts or drills into one domain.
/plan
Plan
Plan a feature or initiative through a computed route — a small fix exits with no documents, one capability gets a spec and a plan, a large initiative gets an umbrella PRD with one spec per capability; start with sdd, sources (market research), iso (regulated work), or research (technical investigation) to run that path directly.
/review
Review
Review branch changes against Archcore docs, or report project health; drift runs staleness detection, deep a full documentation audit, closeout closes a finished feature, experience captures a repeated pattern.
/cite-check
cite-check
Verify that citations actually exist and that the claims they support are faithful to the cited source. Runs deterministic existence checks (Crossref / OpenAlex / Semantic Scholar / arXiv) plus a claim-faithfulness pass via the alterlab-citation-verifier skill.
/lit-review
lit-review
Run a systematic, reproducible literature review on a topic and return an APA 7.0 annotated bibliography with a documented search strategy. Invokes the alterlab-deep-research pipeline in lit-review mode.
/review-paper
review-paper
Run a full multi-perspective peer review of a manuscript, simulating an Editor-in-Chief plus three peer reviewers and a Devil's Advocate, and produce a structured editorial decision and revision roadmap. Invokes the alterlab-paper-reviewer skill.
/research-pipeline
research-pipeline
Orchestrate the end-to-end academic research-to-publication workflow (research, write, integrity check, review, revise, re-review, finalize) with mandatory integrity gates and two-stage peer review. Invokes the alterlab-research-pipeline orchestrator.
/audit-infra
Audit infra
Audit infra security: secrets, deps, CI/CD, webhooks, AI/skill files
/audit-solana
Audit solana
Audit Solana program code for exploitable bugs and write a findings report
/benchmark
Benchmark
Compare per-instruction CU with the stored baseline to catch regressions
/build-app
Build app
Build the web client (Next.js, Vite, React) and check env, types and bundle
/build-program
Build program
Build Solana programs (Anchor, Pinocchio, native), incl. verifiable builds
/build-unity
Build unity
Build the Unity project in batchmode for WebGL, desktop, Android or PSG1
/cleanup
Cleanup
Turn a solana-ai-kit fork into a project: set up CLAUDE.md, remove kit files
/commit-claude-config
Commit claude config
Un-ignore and commit the kit config dir, instruction file, .mcp.json and .gitmodules
/debug-user-tx
Debug user tx
Replay a user's failing transaction on forked state and map the error to source
/deploy
Deploy
Deploy a program to devnet, or to mainnet after the user's explicit go-ahead
/diff-review
Diff review
Review the branch diff for Solana security issues, CU waste and AI slop
/doctor
Doctor
Read-only check of toolchain and kit config, with one fix-it command per failure
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
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