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SkillsMP has collected 192 skills from evolution-foundation/evo-nexus. Open a skill to review its source and details.
evolution-foundation/evo-nexusShowing 40 of 192 collected skills.
Create a Mission, Project, or Goal (Mission → Project → Goal → Task hierarchy) in EvoNexus. Guides the user through picking a mission, choosing or creating a project, defining a measurable goal with metric_type and target_value. Writes to the SQLite goals…
Create a new heartbeat (proactive agent scheduled with a decision prompt) for EvoNexus. Guides the user through picking an agent, setting interval, wake triggers, and the decision prompt that governs when the agent acts. Writes to config/heartbeats.yaml with…
Create a new ticket (persistent conversation/work thread) in EvoNexus. Assigns to an agent, sets priority, optionally links to a goal or project. Writes via POST /api/tickets. Use when the user says 'create a ticket', 'open an issue', 'add to Zara's queue',…
List, enable, disable, or manually trigger heartbeats (proactive agents). Shows last 10 runs with status and cost. Use when the user says 'list heartbeats', 'show active heartbeats', 'enable atlas-4h', 'disable zara-2h', 'run atlas heartbeat now', 'which…
Create, update, list, or run scheduled tasks (one-off actions). Schedule a skill, prompt, or script to run at a specific date/time without creating a full routine. Use when user says 'schedule this for', 'run this at', 'agendar para', 'roda isso amanha',…
Create, manage, and test reactive triggers (webhook & event-based). Triggers execute skills or routines in response to external events (GitHub push, Stripe payment, Linear issue, etc.). Use when user says 'create trigger', 'list triggers', 'novo trigger',…
Generate PNG images using AI (multiple models via OpenRouter including Gemini, FLUX.2, Riverflow, SeedDream, GPT-5 Image, proxied through Cloudflare AI Gateway BYOK). Also analyze/describe existing images using multimodal AI vision. Use when user asks to…
Run Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email…
Autonomous growth experimentation framework. Creates A/B/multivariate experiments with hypotheses, logs data points, runs statistical analysis (bootstrap CI + Mann-Whitney U), auto-promotes winners to a living playbook, and suggests next experiments. Use when…
Score, evaluate, and iteratively improve any content or strategy using an auto-assembled panel of domain experts. Handles copy, sequences, landing pages, strategy docs, titles, charts, recruiting evaluations, or anything else that needs a quality gate.…
AI-powered SEO operations with keyword intelligence, competitor gap analysis, GSC optimization, and trend detection. Use for keyword research, content briefs, quick-win keyword identification, competitor gaps, trending topics, and decaying content analysis.
Write long-form X (Twitter) posts and threads in a founder/CEO voice. Use when drafting X articles, long tweets, thought leadership threads, or viral content. Produces contrarian, data-backed posts with ASCII diagrams and code block visuals. Includes…
Analyze YouTube channels for outlier videos and packaging patterns. Identifies what's working (2x+ average views) across any set of channels. Use when asked for YouTube competitive analysis, viral video patterns, or packaging/title inspiration.
Extract 1–5 atomic facts from pasted text and save them as spaced-repetition cards in workspace/learning/facts/ with SM-2 frontmatter. Use when the user says "capture this", "save fact", "learn this", "memorize this", or pastes content they want to retain.
Generate open-ended quiz questions from facts in a specific deck (or all facts). Read-only — does NOT update SM-2 state or review-log. Use when the user says "quiz", "test me", "pratique", "/learn-quiz", or wants to practice without triggering a formal review.
Review spaced-repetition facts that are due today. Applies SM-2 algorithm to update interval, ease, and next_review in each fact's frontmatter. Updates review-log.jsonl. Use when the user says "revisar", "review facts", "study", or "/learn-review".
Report spaced-repetition statistics: total facts, overdue count, retention rate, active decks, and facts added this week. Use when the user says "stats", "estatísticas", "como está meu aprendizado", "/learn-stats", or wants a dashboard of their learning loop.
Bling ERP integration via API v3. Manage products, sales orders, contacts, fiscal invoices (NF-e), and stock. Use when users ask about ERP data, products, orders, contacts, invoices, or inventory from Bling. Integração com ERP Bling: produtos, pedidos,…
Asaas payment platform integration via API v3. Manage payments (Pix, boleto, credit card), customers, subscriptions, transfers, balance, and marketplace subaccounts. Use when users ask about payment collection, billing automation, Pix, boleto, subscriptions,…
Create a phased activation plan using the EvoNexus standard structure — single index file + folder-per-phase + file-per-item, each item detailed with owner, dependencies, decisions pending, suggested agent team. Use when the user asks for an activation plan,…
Query YouTube Data API v3 — channel stats, recent videos, top videos, comments. Supports multi-account (OAuth or API Key). Use when user asks about YouTube metrics, YouTube channel, subscribers, views, videos, engagement, or any reference to YouTube analytics.
Post-AI-generation cleanup — remove single-use helpers, over-abstractions, generic naming, and unnecessary configurability. Use after dev-autopilot or any LLM-generated code burst.
Advisory router — query Claude, Codex, or Gemini for a quick second opinion. Experimental — only Claude is guaranteed available; other models require dev-mcp-setup configuration.
Tri-model orchestration — run the same task through Claude + Codex + Gemini in parallel and synthesize the best answer. Use for high-stakes decisions where multi-model consensus reduces single-model bias.
Set up Telegram, Discord, or Slack webhooks for engineering layer alerts — long-running task completion, build failures, security audit alerts.
Two-stage investigation — causal trace (via @trail-tracer) followed by requirements crystallization (via @echo-analyst + dev-deep-interview). Use when a problem is both unclear in cause AND unclear in scope.
Deep codebase initialization — generate hierarchical AGENTS.md / CLAUDE.md context files for a new project so engineering agents have full context from session start.
Parallel external documentation lookup. Spawn multiple @scroll-docs agents simultaneously to fetch SDK refs, API docs, and framework guides for different topics in one pass.
Meta-skill — extract reusable skills from the current conversation. Identifies patterns that appeared 3+ times and proposes them as new skills. Pairs with skill-creator builtin.
Configure MCP servers for the workspace — web search, filesystem, GitHub, Stripe, etc. Use when adding a new integration that needs MCP-level access.
Worktree-first development environment — create per-issue or per-PR git worktrees, optionally with tmux sessions, so multiple work streams don't collide.
Persistence loop — keep working on a task until it's resolved or until a circuit breaker stops you. Different from /loop (which is time-based) — ralph is iteration-based with state.
Multi-perspective consensus planning with Planner/Architect/Critic loop. Use when high-stakes decisions need RALPLAN-DR structured deliberation (auth, migrations, public APIs, irreversible changes). Pairs with @compass-planner + @apex-architect +…
Release preparation — changelog generation, version bump, tag creation. Generic version (not project-specific). For EvoNexus releases, use custom-release instead.
Persist context across engineering sessions — save important decisions, gotchas, or patterns that should survive beyond the current conversation. For long-term workspace memory, prefer mempalace.
Scientific method scaffolding — hypothesis → experiment → evidence → conclusion. Use when you need rigorous causal reasoning rather than vibes-based debugging.
On-demand spawning of multiple engineering agents in parallel for large-context work. Use when a task is too big for a single agent and the work can be split into independent streams.
Evidence-driven causal tracing with competing hypotheses. Use when an observation has multiple plausible explanations and you need to systematically rank them with evidence FOR and AGAINST each. Pairs with @trail-tracer.
QA cycling workflow — repeat build/lint/test/fix cycles up to 5 times until all checks pass. Stops early if the same error repeats 3 times (signals a fundamental issue, not a fixable one).
Visual regression testing — capture before/after screenshots of UI changes and compare. Use when a UI change might have unintended visual impact across components.