LLM Mart Basic
@llm-mart · Joined Jun 2026
Execute from repository evidence through applicable UI Spec and optional ADR decisions to complete frontend Design Doc approval
Create frontend work plan from design document and obtain plan approval
Design Doc compliance and security validation with optional auto-fixes
Update existing design documents (Design Doc / PRD / ADR) with review
Separates the outcome a change must produce from the requirements proposed to reach it, records what the user excluded, and bands cost from structure. Use when a requirement enters a workflow, before design begins.
Guides subagent coordination through implementation workflows. Use when orchestrating multiple agents, managing workflow phases, or determining autonomous execution mode.
Implements React/TypeScript unit, integration, and browser E2E tests with the repository's configured runner, mocks, setup, and browser harness. Use when creating or completing frontend tests and generated test skeletons.
Language-agnostic testing principles including TDD, test quality, coverage standards, and test design patterns. Use when writing tests, designing test strategies, or reviewing test quality.
React/TypeScript frontend development rules including type safety, component design, state management, and error handling. Use when implementing React components, TypeScript code, or frontend features.
Applies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend implementation choices, code smells, failures, or implementation completeness.
Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.
Determines which of PRD, ADR, UI Spec, Design Doc, and Work Plan a change requires, and where each is stored. Use when deciding documentation scope, or when creating or reviewing a technical document.
Records where resources outside the repository live (design source, design system, API schema, IaC source, secret store) and how design, implementation, and verification reach them. Use when work depends on an external resource, or when the user mentions design source, design sys
Applies React/TypeScript-specific technical decision criteria, anti-pattern detection, debugging, and frontend quality gates. Use when reviewing components, hooks, browser behavior, or frontend implementation completeness.
Implementation strategy selection framework. Use when planning implementation strategy, selecting development approach, or defining verification criteria.
Integration and E2E test design principles, ROI calculation, test skeleton specification, and review criteria. Use when designing integration tests, E2E tests, or reviewing test quality.
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
Add integration/E2E tests to existing codebase using Design Docs
Execute materialized task files in autonomous execution mode
Execute from codebase-scoped analysis through optional ADR decisions to complete Design Doc approval
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.
/standup
Standup
Daily standup: all 9 departments report on the current project in parallel
/analyze-misfires
analyze-misfires
Identify skills injected where not needed, propose regex and description tightening
/announce
announce
Draft X/Twitter announcement post (or thread) for the latest plugin release
/audit-plugin
audit-plugin
Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste
/diagnose-negatives
diagnose-negatives
Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes
/eval-skills
eval-skills
Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization
/evolve-skill
evolve-skill
Propose a skill revision and compare fresh executions under a frozen rubric
/prune-sync-log
prune-sync-log
Prune stale entries from the whetstone sync decision log
/release
release
Bump version, commit, push, mirror to ai-skills, and update local plugin
/skillopt
skillopt
Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).
/sync-from-repos
sync-from-repos
Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns
/triage-prs
triage-prs
Triage all open PRs with parallel agents, label, group, and review one-by-one
/write-skill
write-skill
Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).
/ia-adr
ia-adr
Create Architecture Decision Records with format selection and lifecycle management
/ia-agent-native-audit
ia-agent-native-audit
Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps
/ia-brainstorm
ia-brainstorm
Explore requirements and approaches through collaborative dialogue before planning implementation
/ia-changelog
ia-changelog
Create engaging changelogs for recent merges to main branch
/ia-deepen-plan
ia-deepen-plan
Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps
/ia-document-release
ia-document-release
Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.
/ia-feature-video
ia-feature-video
Record a video walkthrough of a feature and add it to the PR description
Make any song you can imagine
39 views 0 likesLeading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars
37 views 0 likesHermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research
36 views 0 likesKilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster
34 views 0 likesGeneral-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…
20 views 0 likesAutonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.
20 views 0 likesTSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目
15 views 0 likesCurated, verified Agent Skills powered by ModelStudio.
18 views 0 likesRun Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…
17 views 0 likespi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…
14 views 0 likesA persistent workspace for development work that self-improves and continues beyond one session.
33 views 0 likesOpen-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.
20 views 0 likes📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…
28 views 0 likesDeterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
31 views 0 likesDeterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…
20 views 0 likesNative Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…
34 views 0 likesAgent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
15 views 0 likesGit for agent memory. Branches, diffs, PRs, and rollback for what your agents know.
34 views 0 likesMulti-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…
16 views 0 likesProduction-grade MCP server for MikroTik RouterOS with secure AI-native network automation.
30 views 0 likes