LLM Mart Basic

Use when a Culture Index profile needs comparison with role requirements, team composition, and manager profile for hiring. Not for transcript prediction: use culture-interview-profile-prediction.

Use when asked to predict Culture Index traits from an interview transcript before a survey exists, including sparse or contradictory evidence. Not for interpreting completed survey results.

Use when a manager needs profile-specific communication, one-on-one, motivation, and energy guidance for a direct report. Not for general pair or team compatibility analysis.

Use when a signed new hire's Culture Index profile and team profiles need a first-90-days plan. Not for manager coaching: use culture-manager-coaching.

Use when implementing pool/slab/arena allocators, tuning jemalloc/mimalloc/tcmalloc, writing a Rust GlobalAlloc, or benchmarking allocator performance and fragmentation.

Use when customer feedback, NPS, churn, email feedback, call transcripts, or voice-of-the-customer analysis needs a report over a time window.

Use when the user asks to cut, trigger, or start a release candidate for a release branch. Not for full releases, hotfixes, or non-release-candidate workflow dispatches.

Use when the caller supplies a falsifiable out-of-happy-path invariant and a finite budget. Restores via bounded patches or reverts. Not for normal feature delivery or universal retries.

Use when a build, QA pass, demo, user complaint, or abandoned attempt leaves the next pass needing lessons rather than code. Not for changelog extraction. Not for session handoff: use handoff.

Use when a human-curated dbt model index must guide BigQuery SQL for a warehouse question. Not for discovering undocumented models or executing warehouse changes.

Use when a user asks to tighten verbose-but-correct prose without a full rewrite. Cuts in place to load-bearing density, preserving every load-bearing claim.

Use when debugging RelWithDebInfo or -O2 release builds, using -Og for debuggable optimization, split-DWARF, GDB scheduler-locking, reading inlined frames, or understanding "value optimized out".

Use when the user has a fork and wants it resolved and applied, not explored: "decide this", "choose the path", or "decide and fix it".

Use when a user wants to record why one world won over the others, as a decision-diary entry. Not for remote, credential, publish, deploy, or irreversible changes.

Use when a current decision needs pressure-testing until the rationale is clear to a skeptic. Not for tasks requiring source or remote-system changes.

Use when an imperative program needs pre-conditions, post-conditions, and loop invariants proved automatically by SMT in Dafny or Why3, short of a tactic prover.

Use when asked to deduplicate a skill tree, fold overlapping skills, or cut the skill count: analyze, gate per family, then fold. Not for prompt-doctrine cascades: use cascade-dedup.

Use when the user asks to research a topic and produce a thorough sourced report. Not for remote, credential, publish, deploy, or irreversible changes.

Use when the user wants the finished-system contract for a piece of work: behavior, protocols, allowed, forbidden, and impossible states with a state-space proof. Not for runtime verification.

Turns a song (audio file + lyrics) into a hand-painted watercolour music video (MP4) in the style of PDoomVideo, following its pipeline end to end: measure the beat grid and time the lyrics, scaffold the p5.brush engine, design the story, characters and sets from the lyrics, pain

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.