LLM Mart Basic

Add hard pre-execution guardrails to Claude Code so destructive shell commands are blocked before an agent can run them.

Use CC Safety Net when coding-agent CLIs need pre-execution hooks that block destructive commands, secret access, and unsafe file operations before tools run.

Scan staged changes, commits, or repositories for secrets before they leave the workstation or CI job, instead of relying on a later platform-side catch.

Add a runtime guard that evaluates agent actions, blocks dangerous commands or secret exposure, and audits new skills before they run.

How to use CrystalJson, the custom JSON library in SnowBank.Core (namespace SnowBank.Data.Json). Covers the JsonValue DOM (JsonObject / JsonArray / JsonString / JsonNumber / JsonBoolean / JsonNull / JsonDateTime), the read-only vs mutable model, the CrystalJson static API (Serial

Advanced engineering for sophisticated FoundationDB layers with the .NET client (FoundationDB.Client / SnowBank) — the cluster model and transaction lifecycle (proxies, resolvers, tlogs, storage servers, the sequencer/version clock), latency/throughput optimization (batching read

How to run a FoundationDB cluster and connect to it from .NET — getting the IFdbDatabaseProvider that the keys/transactions/layers skills assume you already have. Covers the ways to get a provider (plain DI services.AddFoundationDb, FdbDatabaseProvider.Create, or Aspire), the Asp

How to correctly encode keys and values, use subspaces and the Directory layer, and write custom "Layers" with the FoundationDB .NET client (FoundationDB.Client / SnowBank). Covers the lazy strongly-typed key structs (subspace.Key(...), FdbTupleKey, FdbRawKey, FdbKey.Increment /

How to correctly run transactions with the FoundationDB .NET client (FoundationDB.Client / SnowBank): the db.ReadAsync / WriteAsync / ReadWriteAsync retry loop and why a handler must be safe to run more than once, the 5-second and size limits, conflicts and how to avoid them, sna

How to guard arguments and assert invariants with the Contract family in SnowBank.Core (namespace SnowBank.Diagnostics.Contracts): the argument guards (Contract.NotNull / NotNullOrEmpty / NotNullOrWhiteSpace / Positive / GreaterThan / GreaterOrEqual / LessThan / LessOrEqual / Equ

How to write, run, and especially DIAGNOSE multi-node integration tests built on the SnowBank distributed-test framework (SnowBank.Testing.Framework / SnowBank.Testing.Common — a general-purpose harness, NOT FoundationDB-specific). Covers DistributedTest/MakeItSo + virtual hosts

How to correctly use the Slice type and its companions (SliceReader, SliceWriter, SliceOwner) for binary data in the FoundationDB .NET client / SnowBank.Core codebase. Slice is a readonly struct (namespace System) — the logical equivalent of a ReadOnlyMemory of bytes with many he

How to use CrystalJson, the custom JSON library in SnowBank.Core (namespace SnowBank.Data.Json). Covers the JsonValue DOM (JsonObject / JsonArray / JsonString / JsonNumber / JsonBoolean / JsonNull / JsonDateTime), the read-only vs mutable model, the CrystalJson static API (Serial

Advanced engineering for sophisticated FoundationDB layers with the .NET client (FoundationDB.Client / SnowBank) — the cluster model and transaction lifecycle (proxies, resolvers, tlogs, storage servers, the sequencer/version clock), latency/throughput optimization (batching read

How to run a FoundationDB cluster and connect to it from .NET — getting the IFdbDatabaseProvider that the keys/transactions/layers skills assume you already have. Covers the ways to get a provider (plain DI services.AddFoundationDb, FdbDatabaseProvider.Create, or Aspire), the Asp

How to correctly encode keys and values, use subspaces and the Directory layer, and write custom "Layers" with the FoundationDB .NET client (FoundationDB.Client / SnowBank). Covers the lazy strongly-typed key structs (subspace.Key(...), FdbTupleKey, FdbRawKey, FdbKey.Increment /

How to correctly run transactions with the FoundationDB .NET client (FoundationDB.Client / SnowBank): the db.ReadAsync / WriteAsync / ReadWriteAsync retry loop and why a handler must be safe to run more than once, the 5-second and size limits, conflicts and how to avoid them, sna

How to guard arguments and assert invariants with the Contract family in SnowBank.Core (namespace SnowBank.Diagnostics.Contracts): the argument guards (Contract.NotNull / NotNullOrEmpty / NotNullOrWhiteSpace / Positive / GreaterThan / GreaterOrEqual / LessThan / LessOrEqual / Equ

How to write, run, and especially DIAGNOSE multi-node integration tests built on the SnowBank distributed-test framework (SnowBank.Testing.Framework / SnowBank.Testing.Common — a general-purpose harness, NOT FoundationDB-specific). Covers DistributedTest/MakeItSo + virtual hosts

How to correctly use the Slice type and its companions (SliceReader, SliceWriter, SliceOwner) for binary data in the FoundationDB .NET client / SnowBank.Core codebase. Slice is a readonly struct (namespace System) — the logical equivalent of a ReadOnlyMemory of bytes with many he

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

Guided component creation with proper patterns

Review existing UI for issues and improvements

Initialize a design system with tokens

Generate unit tests for Python, JavaScript/TypeScript, and React code with mocks, edge cases, and coverage gap analysis

Turn a recorded product demo into a prioritized backlog with timestamped evidence.

Turn one screen recording of a bug into an evidence-backed GitHub issue draft (quote, frames, OCR identifiers, wall-clock; silent recordings work too).

Walk a recording's remarks against system logs using wall-clock timestamps.

Turn a recorded meeting (audio is enough) into action items, decisions, and open questions with timestamps.

Turn a recorded workshop or design walkthrough into a structured spec with quoted decisions and open questions.

Turn a narrated screencast into precise, evidence-backed findings JSON (bug / feature / question routing with frame evidence).

Generate and enforce policy gates for AI coding agents (Copilot, Claude Code) — real-time session hooks that deny protected-path edits and dangerous commands, plus a merge-time backstop for anything that bypasses them. Use when asked to "govern AI agents", "block AI from touching secrets", "add an AI policy gate", or "why did the AI agent hook not fire".

Show the active planning-with-files plan (id, mode, attestation, current phase, phase counts)

Start planning-with-files (task_plan.md, findings.md, progress.md); flags --gated, --autonomous, --template analytics, then an optional plan name

Run a paid-ads (ROAS) workflow: audience segments, account structure, ad creative, experiment design, pre-launch signal QA + the account-audit gate, measurement, and attribution. Not sure? Use /aaron-marketing:auto.

Natural-language front door to the marketing pack (narrative/TALE, SEO/GEO/SITE, social/ECHO, email/SEND, Paid Ads/ROAS, influencer/STAR, launch/RAMP). Use when a marketing goal is open-ended or spans disciplines, when it is unclear which skill fits, or for requests like 'help with our marketing', 'grow our traffic', 'plan our launch', 'what should we post', 'is our messaging landing' — it infers the discipline and runs the smallest useful workflow. Add --deep for exhaustive, maximum-rigor, or stress-test runs.

Run an email-marketing (SEND) workflow: deliverability/consent setup, segmentation, email creative, lifecycle flows, newsletter monetization, send-testing, and the email-quality audit gate. Not sure? Use /aaron-marketing:auto.

Run an influencer-marketing (STAR) workflow: audience & creator scouting, campaign targeting, briefs, outreach, amplification, and ROI reporting. Not sure? Use /aaron-marketing:auto.

Run a product-launch (RAMP) workflow: positioning and launch tiering, window/early-access design, message house and asset kits, the launch-readiness gate with a T-1 go/no-go, launch-day execution, and the post-launch prove loop. Not sure? Use /aaron-marketing:auto.

Run a brand-narrative & messaging (TALE) workflow: trace the current message and positioning truth, architect the durable message house/voice/story canon, land it consistently across every surface, and evaluate resonance with tests and drift monitoring. Not sure? Use /aaron-marketing:auto.

SEO/GEO end-to-end along the SITE loop: survey demand and competitors, implement content, tune quality/tech/on-page, and evaluate authority/rankings/reports/memory (--phase survey|implement|tune|evaluate). Not sure? Use /aaron-marketing:auto.

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.