LLM Mart Basic

Automate Wrike project management via Rube MCP (Composio): create tasks/folders, manage projects, assign work, and track progress. Always search tools first for current schemas.

Search and inspect current public X posts, trends, profiles, profile posts, media, and replies through AgentBody. Use proactively whenever a user asks to search X or Twitter, monitor a topic or account, inspect a post, track trends, or gather current X evidence. Prefer this Skill

Stop an AI agent damaging your repo: PreToolUse hooks, permission deny rules, protected paths, verification gates. Use when "claude keeps force pushing", "CLAUDE.md says X but it still does Y", "stop the agent touching prod or .env", or making a repo safe for unattended agent wor

Find footguns in code that already exists: swappable arguments, silent fallbacks, unguarded deletes, signatures that are easy to misuse. Use when someone asks "what could bite us here", "what is easy to misuse", "poka-yoke this repo", or wants a diff or PR reviewed for ways to ge

Multi-tenant isolation, IDOR and row-level security. Use to find every path where one tenant could read or write another tenant data: "we forgot to filter by org_id", "can users see each other data", "audit these endpoints for cross-tenant leaks", "make an unscoped query impossib

Pipelines, warehouses, dbt models and metrics, where failure is silently wrong numbers rather than a crash. Use when "the dashboard is wrong", "the numbers do not match", "add data quality checks", "safe backfill", or an upstream schema change broke a join. Covers freshness, row-

Design APIs, schemas, types and state machines so misuse cannot be expressed. Use when writing a new interface and someone asks "what should the types look like", "make invalid states unrepresentable", "so callers cannot screw it up", or wants illegal state transitions rejected.

Pre-commit hooks, CI gates, lint rules, database constraints and branch protection. Use when a rule needs enforcing rather than documenting: "set up enforcement", "unformatted or untyped code must not get merged", "gate this in CI", "we agreed to X and people still do not", "stop

AI features you ship to users: structured output, tool schemas, prompt injection, evals. Use when "the model returns bad JSON", "it hallucinates", "stop it calling the wrong tool", "add evals", or an LLM feature can trigger refunds, emails or writes. Covers schema-constrained out

Deploys, schema migrations, rollback and infrastructure. Use when "can I ship this on Friday", "this migration is scary", "what is the blast radius", "prevent accidental deletion of the database", or a change drops a column. Covers expand/contract, canary rollout, kill switches,

Mistake-proofing for anything: code, config, a schema, a process, a runbook, a form. Use when someone says "poka-yoke this", "mistake-proof it", "make this harder to get wrong", or runs /poka-yoke with no mode named. Applies Shigeo Shingo's method directly to any subject, and han

Turn a bug, outage or repeated mistake into a device that makes the whole class impossible. Use when something already broke: "make sure this never happens again", "this is the third time", "postmortem", "how did this get through". Root-causes to the missing constraint, then swee

Forms, destructive actions and flows users get wrong. Use when "users keep deleting the wrong thing", "add a confirmation dialog", "this flow is error-prone", or building a delete, bulk action, checkout or settings page. Covers undo over confirmation, type-to-confirm, safe defaul

Reviewing code that already exists for structural problems: responsibilities that have drifted together, names that no longer describe what they name, dependencies pointing the wrong way, and duplication that has hardened into divergence.

Permission and access-control code. Structure, clarity and testability of authorisation logic: where the decision lives, how it is named, and keeping it separable from the code that acts on it.

Software quality review and design guidance for any code: naming, cohesion, coupling, duplication, function size, dependency direction, and testability. Use when someone asks to improve, review, refactor, or design code, or asks what good structure looks like here. Routes to the

Designing a new interface, module, schema or type. Naming, cohesion, parameter shape, dependency direction and testability, decided before the thing has callers.

Something broke. Deciding what to change in the code so the class of problem is less likely, and writing it up so the next person understands the reasoning rather than just the outcome.

Forms, flows and screens. Structure, naming and clarity of user-facing interaction code: component boundaries, state ownership, and keeping presentation separable from the rules behind it.

Reviewing existing code for unchecked inputs, unguarded dereferences, unhandled failure paths, swallowed exceptions, missing timeouts and absent limits: the places where an unexpected value becomes an unhandled failure.

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

What do I know about a topic

Find and add missing connections

Audit structure and repair what is mechanical

Merge two pages

Record a dated metrics snapshot

The monthly structural review

Find unreachable pages

Outline a piece from your concept pages

Audit what should not be in the vault

Where a project stands

Create a project

Find what is safe to remove

Check what is safe to publish

Test yourself on your own pages

Rename a page and fix every link

Write a research report

Fix a page's type

Periodic review of what the vault learned

Undo the last run

Set up scheduled maintenance

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-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…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP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

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi 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…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.