LLM Mart Basic

Adapt a draft to a user's writing samples or explicit tone brief. Use for consistent personal or project voice across docs and posts; distinguish style evidence from factual content.

Prepare release notes and migration guidance from a verified revision range and project release policy. Use for release preparation; never present open PRs or planned changes as shipped features.

Reduce a reported software bug to a runnable, minimal reproduction with the exact command, environment, and observed failure. Use when verifying a bug report; do not infer success from a failing setup command.

Review a pull request for concrete correctness regressions using its diff, surrounding code, and relevant tests. Use for a requested PR review; distinguish actionable defects from optional preferences.

Review an upstream documentation change against the skills, agent instructions, or runbooks that cite it. Identify supported updates, unaffected instructions, and unresolved version or evidence gaps. Use with a supplied source diff or Skill Watch result.

Turn a repository issue into an evidence-backed triage note: observed behavior, missing reproduction details, possible duplicates, and the next useful action. Use for issue triage, not implementation or bulk issue closure.

Verify a proposed bug fix against an unchanged regression test and the relevant existing tests, reporting baseline and candidate outcomes separately. Use for fix verification, not a general claim that software is bug-free.

Draft factual project announcements, GitHub launch posts, and development updates for a specified audience or platform. Use to explain shipped work clearly, with evidence and a useful invitation for feedback.

Draft clear, respectful replies to issues, PR discussions, and technical support reports from available evidence. Use to explain status, request a minimal reproduction, or communicate a project decision without inventing commitments.

Create or improve a repository README from actual project evidence, with a clear purpose, usable quickstart, and honest limitations. Use for project landing documentation and onboarding, rather than long tutorials or release notes.

Write a focused regression test from an established bug reproduction and public behavior. Use when a fix needs a test that fails on the affected version; avoid mirroring the implementation or weakening assertions.

Build a step-by-step technical tutorial around a reproducible outcome, with prerequisites, checkpoints, and recovery steps. Use for hands-on guides when a README quickstart is too short.

Write or revise interface labels, errors, empty states, and confirmation text from actual product behavior. Use for UI microcopy with clear next actions, preserved localization tokens, and explicit length constraints.

Investigate training failures, NaNs, missing gradients, misleading losses, and non-reproducible runs in PyTorch, Lightning, or TensorFlow/Keras. Use for a concrete training bug or regression, not an open-ended architecture or hyperparameter search.

Edit stiff or AI-sounding prose into natural writing while preserving meaning, facts, citations, and the author's point of view. Use when asked to humanize, de-AI, or make an existing draft sound more human, in its original language.

Translate and localize Polish and English technical documentation, UI text, and project updates. Use for natural PL/EN phrasing while preserving commands, placeholders, factual precision, and a project glossary.

Adapt a draft to a user's writing samples or explicit tone brief. Use for consistent personal or project voice across docs and posts; distinguish style evidence from factual content.

Prepare release notes and migration guidance from a verified revision range and project release policy. Use for release preparation; never present open PRs or planned changes as shipped features.

Reduce a reported software bug to a runnable, minimal reproduction with the exact command, environment, and observed failure. Use when verifying a bug report; do not infer success from a failing setup command.

Review a pull request for concrete correctness regressions using its diff, surrounding code, and relevant tests. Use for a requested PR review; distinguish actionable defects from optional preferences.

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.