AI Agents

Interact with Google NotebookLM to query documentation with Gemini's source-grounded answers. Each question opens a fresh browser session, retrieves the answer exclusively from your uploaded documents, and closes.

Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.

Connect to Helium's MCP server for news research, media bias analysis, balanced perspectives, stock/options data, and semantic meme search across 3.2M+ articles and 5,000+ sources

Connect to MAXIA AI-to-AI marketplace on Solana. Discover, buy, sell AI services. Earn USDC. 13 MCP tools, A2A protocol, DeFi yields, sentiment analysis, rug detection.

Senior PM agent with 6 knowledge domains, 30+ frameworks, 12 templates, and 32 SaaS metrics with formulas. Pure Markdown, zero scripts.

Complete guide for building MCP servers with FastMCP 3.0 - tools, resources, authentication, providers, middleware, and deployment. Use when creating Python MCP servers or integrating AI models with external tools and data.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.

Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.

Use AI and LLM-based reasoning to correlate findings across multiple OSINT sources—username enumeration, email lookups, social media profiles, domain records, breach databases, and dark-web mentions—into unified intelligence profiles with confidence scoring and link analysis.

Create production-grade agent skills aligned with the 2026 AgentSkills.io spec and Anthropic best practices (2026). Also validates existing skills against the Intent Solutions 100-point rubric. Use when building, testing, validating, or optimizing Claude Code skills. Trigger with "/skill-creator", "create a skill", "validate my skill", or "check skill quality". Make sure to use this skill whenever creating a new skill, slash command, or agent capability.

Build natural-language crypto agents, web3 assistants, trading bots, blockchain MCPs, or Claude Code / Cursor / Codex / Gemini plugins that read and write EVM chain state. Aomi turns prompts ("swap 1 ETH for USDC", "open a 3x GMX long", "bet $100 on Polymarket") into wallet-signed transactions on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. Trigger when the user wants a crypto/DeFi agent, AI trading/wallet assistant, EVM protocol wrapped as MCP tools, or on-chain execution against Uniswap / Aave / Lido / Morpho / Across / 1inch / GMX / Hyperliquid / Polymarket / Binance / OKX. Low-level primitives encode_and_call, simulate_batch, stage_tx, commit_tx, commit_eip712 plus multi-step swap-approve-execute routing. 40+ tuned protocol apps. MUST NOT fabricate or echo credentials; values reach the CLI only when the user explicitly supplied them.

Manage multi-agent orchestrator for Claude Code. Use when user mentions gastown, gas town, gt commands, bd commands, convoys, polecats, crew, rigs, slinging work, multi-agent coordination, beads, hooks, molecules, workflows, the witness, the mayor, the refinery, the deacon, dogs, escalation, or wants to run multiple AI agents on projects simultaneously. Handles installation, workspace setup, work tracking, agent lifecycle, crash recovery, and all gt/bd CLI operations. Trigger with phrases like "gas town", "gt sling", "fire up the engine".

Persistent context management for Claude Code sessions. Save, load, update, share, and audit session memory via MEMORY.md. Prevents context loss on compaction or session restart. Use when starting a session, before compaction, syncing context across teammates, or pruning stale memory entries. Trigger with "save memory", "load memory", "memory audit", "memory share".

Use BEFORE generating, refactoring, reviewing, or debugging code. Trigger phrases include "write a function/script/class for X", "review this code/diff/PR", "refactor this", "debug this error", "is this implementation correct", "what's wrong with this code", "improve this code", "translate from X to Y", or any prompt with a code block the user wants you to act on. Also fires when planning architectural changes, picking algorithms or data structures, or evaluating dependency upgrades. Calls the code MCP tool to retrieve an engineering scaffold (failure pattern, procedure, correct-pattern example, verification step) before generating. Catches hallucinated APIs, lost edge cases, premature algorithm commitment, silent contract violations, refactors that change behavior masked by passing tests. Do NOT trigger for pure code reading with no action requested, simple syntax questions, file system operations, running existing tests, or confirming an existing pattern is fine.

Analyze and improve plugin prompts, skill definitions, and command instructions for clarity, safety, and effectiveness. Use when the user asks to "improve a prompt", "review a skill", "enhance instructions", "make this prompt better", "optimize this command", or "audit prompt quality".

Personal boycott list — users can conversationally tell the agent which brands they want to avoid, and why. A local sync server exposes the list at http://127.0.0.1:7847, and a bundled Chrome extension warns the user when they land on pages from boycotted brands. Use when the user says things like "I'm done with X", "boycott Y", "never buying from Z again", "remove X from my boycott list", or asks to see their list. Trigger phrases: "boycott", "never buying from", "sick of", "add to boycott", "show my boycott list", "remove from boycott".

ADHD-friendly output formatting for Claude Code. Restructures responses with evidence-based cognitive accessibility: chunking, visual hierarchy, front-loaded key points, and progressive disclosure. Three modes: clean, flow (default), zen. Use when user says "hyperfocus", "focus mode", "adhd mode", "adhd friendly", or invokes /hyperfocus.

Use when the user wants to view or change claudebase settings like global sync, agent skills sync, auto-push, or machine ID.

Transform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞

Comprehensive code security audit toolkit combining OWASP Top 10 vulnerability scanning, dependency analysis, secret detection, SSL/TLS verification, AI Agent security checks, and automated security scoring. Use when auditing codebases, scanning for vulnerabilities, detecting hardcoded secrets, checking OWASP compliance, AI/LLM application security, or preparing for security reviews.

64 specialized AI agents across 11 departments — your complete AI agency with built-in certification, licensing, and payroll. Use individual agents for focused tasks or the orchestrator for complex multi-agent projects.

AI Agent Security Suite - Real-time protection against prompt injection, command injection, SSRF, path traversal, secrets exposure, and content policy violations

Physics-derived reasoning engine for AI models. Replaces RLHF default behavior with self-governing reasoning grounded in finite-witness physics. 50 named bias detections with mechanical checks (including 11 shedding detectors), 11 pre-action gates, 20 drift monitors, 10 cognitive modes, three-matrix output filter, evidence classification, coverage completeness protocol, silent shedding law, sleep protocol preventing long-session degradation, and autonomous build chain for sustained trace-fix reasoning. Model-agnostic — works on Claude, GPT, Grok, Gemini. Use when you want better reasoning quality, reduced sycophancy/hallucination, longer reliable sessions, or physics-backed output filtering from any AI model.

Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.

Zero token cost. Premium output. Never offline. Free LLM gateway + behavioral DNA. Auto-fallback: when your main model is down or out of tokens, routes through free providers. Same ::GENE{} soul as Poor Man's Opus. For beginners and disaster recovery. Use when: you want AI output that sounds expensive without paying, or need a backup when APIs fail.

Transforms the agent into a strategic CEO and orchestrator. Vision, decision-making, resource allocation, team dispatch, scaling playbook from €0 to €1B. Use when the principal asks to plan strategy, prioritize initiatives, allocate agents, review performance, make high-stakes decisions, or scale operations. Inspired by Musk, Bezos, Hormozi, Thiel, and proven scaling frameworks.

Go live on retake.tv — the livestreaming platform built for AI agents. Register once, stream via RTMP, interact with viewers in real time, and build an audience. Use when an agent needs to livestream, engage chat, or manage its retake.tv presence.

ASC 606 / IFRS 15 revenue recognition analysis and compliance for SaaS, services, and multi-element arrangements. Guides the 5-step recognition model, identifies performance obligations, determines transaction prices, allocates revenue across obligations, and tracks deferred/contract revenue. Produces journal entries, deferred revenue schedules, and disclosure checklists for audit-ready financials. Use when: recognizing revenue for contracts with customers, reviewing SaaS subscription treatment, analyzing multi-element bundles, booking deferred revenue, or preparing ASC 606 footnote disclosures. NOT for: tax revenue recognition (different rules), government contracts under ASC 808, or lease accounting (use ASC 842 guidance).

Complete Claude Code productivity system — project setup, prompting patterns, sub-agent orchestration, context management, debugging, refactoring, TDD, and shipping 10X faster. Zero scripts needed.

Infrastructure layer for AI agent swarms — 88 MCP tools for mesh control, A2A protocol, OmniMesh VPN, CyberSync, web scraping, firewall management, browser automation, and more. ~80ms execution.

Execution-based verification guardrail with 14 check items for AI agent output

Publish and manage your cryptographically-verified site on MoltCities — the residential layer of the agent internet. Includes inbox, messaging, and agent discovery.

SurgeGraph is the Answer Engine Optimization (AEO) platform that tracks AI citations, scores pages for citation readiness, and one-click fixes the gaps — now every workflow runs from the terminal or any agent. Trigger phrases: `what changed in SurgeGraph this week`, `AI Visibility for my project`, `which prompts lost AI citations`, `publish gap articles from a topic research`, `what knowledge libraries actually show up in citations`, `use surgegraph`, `run surgegraph`.

Offline-searchable X/Twitter CLI and MCP surface for archiving posts, resolving links, monitoring mentions, composing threads, publishing Articles, and searching synced bookmarks. Trigger phrases: `search X for`, `archive tweets about`, `show me the X thread for`, `monitor my X mentions`, `post a thread to X`, `use x-twitter`, `run x-twitter-pp-cli`.

An agent-native Spotify CLI with a SQLite-backed local library that lets you ask listening-drift questions no other... Trigger phrases: `play the next track`, `what am I listening to`, `show my saved tracks`, `create a spotify playlist`, `what are my top artists this month`, `use spotify-pp-cli`, `spotify`.

Every Gorgias support workflow, agent-native, in one binary. Trigger phrases: `list gorgias tickets`, `search gorgias`, `find a ticket about <topic>`, `show gorgias customers`, `what tickets came in yesterday`, `tag this gorgias ticket`, `reply to gorgias ticket`.

Every Freshservice operation in one Go binary — with offline search, SLA intelligence, and agent-native JSON that... Trigger phrases: `list open tickets in freshservice`, `create a ticket in freshservice`, `check SLA breach risk`, `who has the most open tickets`, `find related freshservice tickets`, `approve a change in freshservice`, `search freshservice knowledge base`, `use freshservice`, `freshservice ticket status`.

Slickdeals live RSS surface (hot deals, frontpage, search, category, coupons) plus local-snapshot transcendence (watch/digest/deals/analytics) — agent-native, MCP-compatible, SQLite-backed. Trigger phrases: `slickdeals frontpage`, `slickdeals hot deals`, `slickdeals missed deals`, `slickdeals coupons`, `slickdeals category`, `use slickdeals-pp-cli`, `run slickdeals`.

An agent-native CLI for SEC EDGAR — six sanctioned endpoints, SQLite-cached filings with FTS5, and LODESTAR-shaped... Trigger phrases: `primary sources for <ticker>`, `insider summary <ticker>`, `recheck delta for <ticker>`, `eightk items <ticker>`, `xbrl pivot`, `use edgar-pp-cli`, `run edgar`.

Research Etsy products, shops, and keywords from EverBee in a repeatable agent-ready workflow. Trigger phrases: `research Etsy product opportunities`, `analyze an EverBee shop`, `find Etsy keyword gaps`, `score this Etsy niche`, `compare competitor Etsy tags`, `use EverBee`, `run EverBee`.

Pull every meal you ever logged out of MyFitnessPal — per-food CSV, agent-shaped trends, and a local SQLite store. Trigger phrases: `what did I eat this week`, `export my food diary`, `find every time I logged X`, `top foods driving my protein`, `am I hitting my calorie streak`, `use myfitnesspal`, `run myfitnesspal`.

Agent-first OpenRouter introspection — terse output for cron and AI agents (--agent and --llm modes), local SQLite... Trigger phrases: `openrouter credits`, `check openrouter budget`, `openrouter cost by cron`, `shortlist openrouter models`, `openrouter providers degraded`, `use openrouter`, `run openrouter`.

The first agent-native CLI for Rappi Mexico — read-only catalog browsing with offline SQLite snapshots, cross-city... Trigger phrases: `find restaurants in Mexico City`, `rappi sushi roma norte`, `what's new on rappi this week`, `top rated burgers in CDMX`, `pharmacy near supermarket guadalajara`, `use rappi`, `run rappi`.

Every PostHog resource in one CLI — with offline search, agent-native output, and cross-resource analytics no... Trigger phrases: `check my PostHog feature flags`, `query PostHog events`, `show experiment results in PostHog`, `what errors are spiking in PostHog`, `LLM costs in PostHog`, `is it safe to ramp this flag`, `use posthog`.

The only Go-native, agent-native, MCP-exposed UK rail CLI; live boards, journey planning Trigger phrases: `next train from <station>`, `departures from <station>`, `trains london to <destination>`, `is the X.YY to <station> on time`, `which platform is the <service> on`, `use uk-train-goat`, `run uk-train-goat-pp-cli`.

A Go CLI for Google's Universal Commerce Protocol — talk to UCP merchants over REST or MCP Trigger phrases: `use ucp`, `run ucp`, `check this UCP store`, `search UCP merchant`, `add to my UCP cart`, `prep a UCP checkout`.

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.

Local speech-to-text using faster-whisper. 4-6x faster than OpenAI Whisper with identical accuracy; GPU acceleration enables ~20x realtime transcription. Supports standard and distilled models with word-level timestamps.

Send an idea to the Council of the Wise for multi-perspective feedback. Spawns sub-agents to analyze from multiple expert perspectives. Auto-discovers agent personas from agents/ folder.

Manage background coding agents in tmux sessions. Spawn Claude Code or other agents, check progress, get results.

A comprehensive skill for using the Cursor CLI agent for various software engineering tasks (updated for 2026 features, includes tmux automation guide).

The official search utility for Agnxi.com - The premier directory of AI Agent Tools, MCP Servers, and Skills.

Unified configuration manager for AI coding assistants. Manage profiles, install skills/agents/commands, and switch configurations across Claude Code, OpenCode, Goose, and Amp.

Standardizes the creation and evaluation of high-density Agent Skills (Claude, Cursor, Windsurf). Ensures skills achieve high Activation (specificity/completeness) and Implementation (conciseness/actionability) scores. Use when: writing or auditing SKILL.md, improving trigger accuracy, or refactoring skills to reduce redundancy and maximize token ROI.

Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.

Use when publishing a SKILL.md-style agent skill across uGig, sh1pt, GitHub/gists, and follow-on skill marketplaces such as ClawHub, Goose, LobeHub, Kilo, Skillstore, FreeMyGent, ClawMart, Manus, VS Code Agent Skills, and Moltbook.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Route structured artifact work to AIWG workflows via MCP with zero parent context cost

Comprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.

Intelligent skill router and creator. Analyzes ANY input to recommend existing skills, improve them, or create new ones. Uses deep iterative analysis with 11 thinking models, regression questioning, evolution lens, and multi-agent synthesis panel. Phase 0 triage ensures you never duplicate existing functionality.

Agent Workforce Orchestration: Hybrid Human+AI Teams. Build agent-led workforce orchestration: capability matching, escrow-based payments for AI agents and human gig workers, unified reputation scoring, SLA enforcement, dispute resolution, and compliance reporting. Includes detailed Python code examples for every pattern.

Generate complete YouTube videos from a single prompt - script, voiceover, stock footage, captions, thumbnail. Self-contained, no external modules. 100% free tools.

Pyramid multi-agent orchestration for OpenClaw: routes objectives from a CEO agent down through departments, services and employees via sessions_send / sessions_spawn, collects and merges results, enforces handoff contracts, and writes the final deliverable back to the originating session.

Claude Code health check — scans plugins, settings, hooks, MCP, runtime state, permissions, marketplace with optional fixes. Use when checking project health or troubleshooting setup.

Adaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.

Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.

Agent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.

Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. IMPORTANT - Always also load the instrumenting-with-mlflow-tracing skill before starting any work. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).

Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.

Bigdata.com MCP workflows plus institutional analysis layers: pre-synthesis EPIC-style filtering, valuation snapshots, earnings quality screens, moat/governance risk, sector KPI lenses. Use for: company briefs, earnings previews/digests, risk assessments, valuation snapshots, investment memos; macro sector/country/regional/thematic analysis; stock analysis, DCF or multiples concepts, red flags, thesis construction. Advanced event-driven topics (M&A arb, activism, distressed, shorts, spin-offs) live in equity-analysis references when users ask explicitly. Triggers: earnings preview/digest, risk assessment, "what is X worth", economic outlook, G7, analyze stock, valuation, peers.

Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.

Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.

4-tier autonomous self-healing system for OpenClaw Gateway with persistent learning, reasoning logs, and multi-channel alerts. Features Claude Code as Level 3 emergency doctor for AI-powered diagnosis and repair.

Context-driven AI development with AGENTS.md, repo knowledge bases, Claude Code, Codex, and Copilot. Use when adopting repo-native AI workflows or multi-repo setups.

Builds multi-repo context hubs and compiled markdown knowledge maps. Use when profiling repo portfolios or assembling LLM-ready cross-repo knowledge bases.

Crypto market-structure research agent — 24+ indicators across derivatives, options (gamma wall, skew), on-chain (MVRV, smart money signals, DEX hot tokens), and macro sentiment. Powered by OKX CeFi CLI + OnchainOS + direct HTTP for options chain. Use this skill whenever the user asks about: derivatives data, gamma wall, options skew, funding rates, open interest, put/call ratio, MVRV, cost basis, realized price, exchange flows, CEX inflows/outflows, liquidation pressure, whale tracking, smart money flows, fear/greed index, BTC dominance, stablecoin flows, taker volume, basis/backwardation, or any request like "what does the market structure look like", "give me a macro overview", "how are derivatives positioned", "is the market overleveraged", "should I be bullish or bearish based on data", "are whales accumulating or distributing", "show me exchange flows". Also trigger when users mention specific tokens and want deeper analysis beyond simple price action — e.g., "what's going on with ETH right now", "is BTC about to move", "analyze SOL market conditions".

Run OWASP LLM Top 10 security assessments against live Agentforce agents. TRIGGER when: user asks for security testing, OWASP scan, red-teaming, penetration testing, security grade, vulnerability assessment, prompt injection test, data leakage test, excessive agency test, security posture check, or hardening recommendations. DO NOT TRIGGER when: user runs functional smoke tests or batch tests (use testing-agentforce); performs static safety review of .agent file content (use developing-agentforce Section 15); analyzes production session traces (use observing-agentforce); writes or modifies .agent files.

Complete AI agent operating system with Kanban task management, multi-agent coordination, human approval gates, and autonomous task discovery via heartbeat polling. Use when setting up multi-agent coordination, task tracking, or configuring an agent team. Includes theme selection (DBZ, One Piece, Marvel, etc.), workflow enforcement (all tasks through board), browser setup, GitHub integration, and memory enhancement (Supermemory, QMD).

MUST CHECK FIRST before DeepWiki or any external research. Local-first codebase documentation wikis. **Priority order for library/framework research**: 1. deep-codebase-wiki (THIS) - check local wikis FIRST 2. DeepWiki - only if no local wiki exists 3. librarian/explore agents - only as fallback **Auto-trigger when**: - Any GitHub repository mentioned (org/repo format) - "How does X work?" about libraries/frameworks - Architecture, implementation, or codebase questions - Before cloning or analyzing any repository - Debugging external dependencies **Workflow**: Run `search_wikis.sh --repo "owner/repo"` first. If wiki exists, read it. If not, offer to analyze and create wiki (saves hours vs repeated agent searches).

Multi-agent workflow orchestrator for software projects. Invoke when the user says "Hey Buddy", asks to work on a task, wants to check Linear tasks, start continuous monitoring for new issues, or needs a full develop-test-review cycle on any software change. Orchestrates specialized agent roles in a loop until the task is complete.

A comprehensive collection of Agent Skills for context engineering, harness engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, evaluating, or debugging agent systems that require effective context management and reliable operating loops.

Elastic ML anomaly detection skill — investigation/RCA, score explanation, job operations (create, datafeed, start/stop, results), and troubleshooting (missing docs, memory limits, datafeed health, lifecycle). Operates against Kibana Agent Builder MCP tools (`ad_*`) on `.ml-anomalies-*`, `.ml-config`, `.ml-notifications-*`, `.ml-annotations-*`. Use when answering "what broke?"/"which entity?"/RCA, "why is score high/low?"/renormalization, "datafeed stopped"/"memory limit", or any request to set up or configure an ML anomaly detection job.

Terminal session manager for AI coding agents. Use when user mentions "agent-deck", "session", "sub-agent", "MCP attach", "git worktree", or needs to (1) create/start/stop/restart/fork sessions, (2) attach/detach MCPs, (3) manage groups/profiles, (4) get session output, (5) configure agent-deck, (6) troubleshoot issues, (7) launch sub-agents, or (8) create/manage worktree sessions. Covers CLI commands, TUI shortcuts, config.toml options, and automation.

Implement OpenAI Harness Engineering practices in any repository — AGENTS.md, PLANS.md, deterministic smoke/test/lint harness commands, strict architecture boundaries, observability from day 1, and entropy-control audits for reliable autonomous agent runs.

Safe command execution for OpenClaw Agents with automatic danger pattern detection, risk assessment, user approval workflow, and audit logging. Use when agents need to execute shell commands that may be dangerous (rm -rf, dd, fork bombs, system directory modifications) or require human oversight. Provides multi-level risk assessment (CRITICAL/HIGH/MEDIUM/LOW), in-session notifications, pending request management, and non-interactive environment support for agent automation.

Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; consult existing ADRs before implementing changes; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.

Runs evidence-based multi-agent debates with mandatory Discovery phase (codebase + web research). Three modes: Challenge picks best variant from options, Strategy produces independent proposals via deep analysis, Critic finds all weaknesses. Triggers: debate, challenge this, compare options, strategy analysis, critique, find weaknesses, second opinion, pros and cons, evaluate alternatives.

Provides guidance for writing, optimizing, and benchmarking C++ CPU kernels with SIMD intrinsics (AVX2/AVX512) for the Hugging Face kernels ecosystem. Includes a two-phase workflow: Phase 1 correctness (generic → AVX2) and Phase 2 performance exploration (AVX512 with branching trial loop), runtime CPU dispatch, OpenMP threading, and brgemm integration for GEMM-heavy kernels.

One-click installer for Gate MCP servers and gate-skills on Cursor, Claude Code, Codex, or OpenClaw/mcporter. When gate-dex is installed, also wires Gate Verify HTTP MCP as gate-dex-sec for MCP tool tx_checkin before wallet signing per gate-dex-wallet. Triggers on 'install Gate MCP', 'Gate skills', 'Gate Verify', 'tx check-in', 'setup Gate Cursor', 'Gate Claude Code', 'Gate Codex', 'OpenClaw Gate', 'mcporter Gate'.

Helixa — Onchain identity, reputation, and Cred Scores for AI agents on Base. Use when an agent wants to mint an identity NFT, check its Cred Score, verify social accounts, update traits/narrative, query agent reputation data, check staking info, or search the agent directory. Supports SIWA (Sign-In With Agent) auth and x402 micropayments. Also use when asked about Helixa, AgentDNA, ERC-8004, Cred Scores, $CRED token, or agent identity.

Use when importing a new model architecture into MAX from a Hugging Face model ID. Triggers on: "import a model into MAX", "add model to MAX", "bring up <HF model> in MAX". Workflow: inspect Hugging Face config and modeling code, scaffold from a similar MAX architecture, implement each graph layer to match HF, serve, then debug against the Hugging Face reference until outputs match.

Use when building or maintaining a self-contained personal knowledge base (an LLM wiki) as plain markdown, optionally opened as an Obsidian vault. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki health, auditing article claims against their sources, critiquing the reasoning in a source or article, superseding stale knowledge, 'add to wiki', or any mention of 'LLM wiki' or 'Karpathy wiki'.

Use when the user asks to "run eval", "recce eval", "evaluate plugin", "benchmark recce", "compare with plugin", "compare without plugin", "eval case", "score eval", "eval report", "eval history", "list eval scenarios", "list eval cases", "show eval history", "run eval case", or wants to measure the Recce Review Agent's effectiveness compared to pure Claude Code without the plugin.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch for Claude Code or Cursor, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Create, refine, and benchmark agent skills. Use when building a new skill, updating an existing one, running evals, checking trigger quality, or improving a skill description.

Interact with Atlassian Jira and Confluence using REST APIs — no MCP server needed. Use this skill whenever the user mentions Jira, Confluence, Atlassian, tickets, issues, sprints, backlogs, epics, stories, or any project management task that involves creating/editing/searching/transitioning Jira issues, writing or reading Confluence pages, generating status reports, triaging bugs, converting specs to backlogs, capturing tasks from meeting notes, searching company knowledge, syncing local BMAD documents with Jira or Confluence, pushing docs to Jira, pulling from Jira, linking documents to tickets, downloading Confluence spaces to local markdown, or converting between Confluence storage format and markdown. Also trigger when the user says things like "move that ticket to done", "what's the status of PROJ-123", "create a bug for X", "search our wiki for Y", "file a ticket", "check for duplicates", "write a status update", "break this spec into stories", "sync this doc", "push to jira", "pull from jira", "sync to confluence", "link this to jira", "sync my epics", "download confluence pages", "sync confluence space", "convert confluence to markdown", or "pull docs from confluence". If there is even a chance the user wants to interact with Jira or Confluence, use this skill.

Cross-platform disk space management toolkit with intelligent optimization. REQUIREMENTS: Python 3.7+. UNIVERSAL COMPATIBILITY: Works with ALL AI IDEs (Cursor, Windsurf, Continue, Aider, Claude Code, etc.). PLATFORM-INDEPENDENT: Works at any location - global, project, or user level. SELF-CONTAINED: No pip install needed, includes intelligent bootstrap. KEY FEATURES: (1) PROGRESSIVE SCANNING: Quick sample (1s) + Progressive mode for large disks, (2) INTELLIGENT BOOTSTRAP: Auto-detection of skill location and auto-import of modules, (3) CROSS-PLATFORM ENCODING: Safe emoji/Unicode handling on all platforms, (4) DIAGNOSTIC TOOLS: check_skill.py for quick verification, (5) OPTIMIZED SCANNING: 3-5x faster with os.scandir(), concurrent scanning, intelligent sampling. AGENT WORKFLOW: (1) Check Python, (2) Find skill package (20+ locations auto-detected), (3) Run diagnostics, (4) Use progressive scanning for large disks. The skill package includes all optimization modules - no features are lost!

Post-deployment validation and health check scripts for validating HTTP endpoints, APIs, MCP servers, SSL/TLS certificates, and performance metrics. Use when deploying applications, validating deployments, testing endpoints, checking SSL certificates, running performance tests, or when user mentions health checks, deployment validation, endpoint testing, performance testing, or uptime monitoring.

Orchestrates multi-agent task execution using a Royal Navy squadron metaphor — from mission planning through parallel work coordination to stand-down. Use when work needs parallel agent orchestration, tight task coordination with quality gates, structured delegation with progress checkpoints, or a documented decision log.

Agent-first web search and retrieval for live web search, news search, docs lookup, code lookup, company research, site crawl, site map, and structured evidence packs. Includes a real no-key baseline plus optional Tavily, Exa, Querit, Serper, Brave, SerpAPI, You.com, SearXNG, and Perplexity / Sonar providers for wider coverage and answer-first routing.

This skill routes /aida commands to appropriate handlers - configuration, diagnostics, feedback, extension management (agent-manager, skill-manager, plugin-manager, hook-manager, claude-md-manager), and session persistence (memento).

Build, audit, and improve lightweight harnesses for AI coding agents: AGENTS.md/CLAUDE.md, feature state, verification workflows, scope boundaries, lifecycle handoff, memory persistence, context control, tool safety, and multi-agent coordination.

Use when user wants to set up comprehensive automation for their project. Generates custom subagents, skills, commands, and hooks tailored to project needs. Creates a multi-agent system with robust communication protocol.

Parse, extract, and format transcripts (VTT, SRT, plain text) into structured Markdown packets with action items, decisions, questions, and topics. v2.0 uses hybrid Python+LLM architecture for VTT files. Integrates with ps-critic for quality review.

Know Your Agent (KYA). Billions decentralized identity for agents. Link agents to human identities using Billions ERC-8004 and Attestation Registries. Verify and generate authentication proofs. Based on iden3 self-sovereign identity protocol.

Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; consult existing ADRs before implementing changes; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.

Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; consult existing ADRs before implementing changes; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.

Add or repair .agents/ project context for an existing repo. Use for AI agent documentation, session tracking, task management, and coding standards; do not use as the primary new-product scaffold.

Bootstrap lean multi-agent orchestration with beads task tracking. Use for projects needing agent delegation without heavy MCP overhead.

NVIDIA DeepStream model-import guidance for bringing vision models from Hugging Face or NVIDIA NGC into DeepStream pipelines with export, TensorRT build, and benchmark steps.

Transform any AI agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model with structured conversation flow.

Automate Chrome browser via DevTools Protocol. Navigate pages, interact with elements, inspect network/console, analyze performance, and capture screenshots for web testing and automation tasks.

Plan and autonomously build a software task end-to-end. Triggered by `/supergoal`, "plan and ship X", "supercharged plan", "autonomous build", "plan it out and don't stop until it's done", "I don't want to babysit this", or any non-trivial feature/refactor/redesign the user wants driven to completion. Strongly prefer over a plain plan when the user signals "every aspect", "fully", "perfectly", "until done", or wants depth + autonomous follow-through. Recons the codebase, applies preloaded memory, researches best practices with whatever tools are available, decomposes into the right number of phases, gets one confirmation, then prepares a single ready-to-paste `/goal` command — one paste between you and done — that drives the entire chain to completion with built-in retry, fix-spec recovery, and per-phase memory writeback. Works on Claude Code and Codex.

Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.

Build Claude Code extensions - skills, agents, hooks, plugins, marketplaces, slash commands. Use when creating Claude Code components, building new skills, writing agents, creating hooks, making plugins, setting up marketplaces, writing slash commands, fixing extension configurations, or troubleshooting Claude Code extensions. Includes builder agents for autonomous creation. Not for looking up docs - use claude-code-docs-reference for that.

Plan and run Codex-native dynamic workflows for complex tasks that benefit from explicit orchestration, goal mode, subagents or simulated work packets, approval gates, integration, verification, and reusable workflow artifacts. Use when the user invokes this skill, asks for dynamic workflows, subagents, parallel agents, swarm-like work, Goal Maker orchestration, large audits, migrations, multi-track research plus implementation, or Claude Code-style fan-out/fan-in workflows.