LLM Mart Basic

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.

Defensive programming for any code: validating inputs at every boundary, checking for null and absent values, supplying safe fallbacks, catching and logging exceptions, and degrading gracefully rather than failing. Use when someone asks to make code robust, resilient, safer, or h

Designing a new interface, module, schema or type together with its validation and failure behaviour: what each input accepts, what happens when it does not, and what the caller gets back when something goes wrong.

微信读书读后感写作助手。帮助用户基于某本书或某个章节，生成一篇带有个人见解的读后感，正文严格控制原文摘抄，附录完整保留所有划线内容及即时感想。底层依赖 weread-skills（微信读书原子 API）和 huashu-weread-advisor（微信读书高阶顾问工作流）。当用户说「写一篇读后感」「帮我整理笔记写感想」「这本书/这章我想写篇公众号文章」时触发。

A green PR, a controller reporting success, and not one line of the new code running

Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values

Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json

Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.

Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.

Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement

Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories

Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples

Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers

Orchestrate git workflow from code review through PR creation with quality gates

Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning

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.