All Skills

Use to design a safe pipeline that writes derived attributes back into a helpdesk — risk scores, segments, health flags — without corrupting agent workflows or creating an unexplainable feedback loop. Trigger for "push scores back into Zendesk", "sync warehouse attributes to the helpdesk", "write our churn risk onto the ticket", reverse ETL for support, or an automation that started firing on a synced field.

Use to measure whether a support bot, AI agent, or self-service channel actually reduces contact volume, and to audit a vendor's containment or deflection number. Trigger for "what's our real deflection rate", "is the bot working", "our containment rate is 70% but tickets haven't dropped", automation ROI, self-service savings, AI agent resolution rate, or designing a holdout test for a support bot.

Use to write CX commentary that makes a number decision-ready — what moved, why (decomposed), so what, do what — separating noise from signal and stating confidence honestly. Trigger for "write the commentary", "explain this trend", "what should we say about the drop", weekly or monthly narrative, board pack prose, "why did QA fall", metric movement write-up, or when a report has charts but no story.

Use to design the process that gets a revenue signal out of support and to the account owner without turning agents into sellers or degrading support quality. Trigger for "route upsell leads from support to sales", "support-sourced pipeline process", "should agents flag opportunities", designing a CS-to-sales handoff, or a handoff programme where agents have stopped flagging.

Use to design overnight and follow-the-sun support — coverage models, handoff quality and measuring what is lost between shifts. Trigger for "after-hours coverage", "follow the sun", overnight support design, night shift vs defer async, handoff packet, shift handover quality, global coverage gaps, or when customers reopen tickets after every handoff.

Use to keep localised help centre content current when the source language changes, detect stale translations, and prevent silent lag between markets. Trigger for "translations are out of date", localisation workflow, source of truth language, help centre i18n, translation drift after policy update, or non-English customers seeing old policy.

Use to measure which help articles actually resolve contacts versus merely being read, including contact-after-view and assisted resolution. Trigger for "are our help articles working", article view counts misleading, deflection measurement, contact after reading an article, self-service success metrics, KB ROI, or stopping AI agents from optimising for page views.

Use to build and maintain a reusable bank of QA criteria as observable decision rules shared across scorecards. Trigger for "criterion library", "standardise our QA criteria", "write better rubric items", "was professional is too vague", versioning criteria across teams, or turning adjectives into pass/fail decision rules with examples.

Use to find where support agents cross from information into regulated advice or a personal recommendation, and to design the boundary so they can still be helpful. Trigger for "are agents giving advice", "where's the line between information and advice", "should agents recommend a product", guidance versus advice boundary, agents answering "what would you do", or a complaint that an agent recommended something.

Full-novel craft + anti-slop pipeline with project mode (ledger, characters, foreshadow, worldbuilding bible), draft→review→revise gates, and stability-trap enforcement at scene/chapter/manuscript scale. Single-scene mode retained. Use for fiction, lore, character docs, dialogue, worldbuilding, or book projects.

Fast vector similarity search at billion scale.

Systematic methodology for auditing the Hermes Skills Hub (and external sources) to identify gaps, overlaps, redundancies, and conflicts when building a skill library for any project. Covers browsing, targeted searching, cross-referencing with web/GitHub, comparing candidates against existing inventory, verifying install safety, and planning installation order. Use when starting a new project and assembling tools, or when evaluating whether to add external skills beyond what's currently installed.

Interact with the Last.fm music data API: lookup user listening history, get artist/album/track metadata, discover similar music via collaborative filtering, explore global and per-country charts, search by artist/album/track, manage tags, and scrobble listening events. Use when the user asks about music data, listening statistics, music recommendations, similar artists, charts, or wants to scrobble or love tracks.

Operate, configure, provision, secure, and troubleshoot Grafana OSS, Enterprise, and Cloud, including dashboards, folders, data sources, annotations, alert rules, contact points, notification policies, silences, mute timings, service accounts, RBAC, plugins, APIs, and as-code workflows. Use for Grafana product work and Grafana-side integrations. Do not use for defining SLOs or paging policy, operating Prometheus/Loki/Tempo/InfluxDB backends, generic Docker/Kubernetes/Terraform/reverse-proxy work, plugin development, or authorized security assessments; use the corresponding specialist skill.

Implement the Entrepreneurial Operating System (EOS) to align vision and execution across a company. Use when the user mentions "EOS", "V/TO", "quarterly rocks", "Level 10 meetings", "accountability chart", "IDS process", "Entrepreneurial Operating System", or "business operating system". Also trigger when a growing company needs meeting structure, goal-setting frameworks, or a systematic approach to solving recurring organizational issues. Covers the six EOS components: Vision, People, Data, Issues, Process, Traction. For team motivation design, see drive-motivation. For lean experimentation, see lean-startup.

Search and discover movies, TV shows, and trending content via The Movie Database (TMDb) API v3. Use when the user asks about movies, TV, film, cinema, genres, certifications, ratings, cast, upcoming releases, or trending media.

Evaluate and improve interface usability using heuristic analysis. Use when the user mentions "usability audit", "UX review", "users are confused", "heuristic evaluation", "form usability", "navigation problems", "Nielsen heuristics", "cognitive walkthrough", or "usability testing". Also trigger when reviewing a design for usability issues, improving form completion rates, or evaluating information architecture and navigation. Covers Nielsens 10 heuristics, severity ratings, and information architecture. For visual design fixes, see refactoring-ui. For conversion-focused audits, see cro-methodology.

Stock quotes, history, search, compare, crypto via Yahoo.

Design motivation systems using Autonomy, Mastery, and Purpose (AMP) for products and teams. Use when the user mentions "intrinsic motivation", "gamification isnt working", "team incentives", "autonomy", "mastery", "purpose-driven", "employee engagement", or "reward systems". Also trigger when designing onboarding progression systems, fixing broken gamification, or building team structures that sustain high performance. Covers why carrot-and-stick fails and how to build progress systems. For habit-forming product loops, see hooked-ux. For retention behavior design, see improve-retention.

Structure software around the Dependency Rule: source code dependencies point inward from frameworks to use cases to entities. Use when the user mentions "architecture layers", "dependency rule", "ports and adapters", "hexagonal architecture", "use case boundary", "onion architecture", "screaming architecture", or "framework independence". Also trigger when decoupling business logic from databases or frameworks, defining module boundaries, or debating where to put business rules. Covers component principles, boundaries, and SOLID. For code quality, see clean-code. For domain modeling, see domain-driven-design.

Deploy, configure, and manage CrowdSec — the open-source, collaborative IPS/IDPS/WAF. Covers Security Engine setup (Linux, Docker), cscli hub management, remediation components, AppSec WAF, profiles, notifications, blocklists, CTI, and metrics. Use when setting up or troubleshooting CrowdSec.

Build type-safe AI agents and graph-based workflows with PydanticAI and PydanticGraph. Agent creation, function tools, capabilities, dependency injection, structured output, streaming, multi-agent patterns, testing, evals, and graph state machines. Use whenever you are building agents, tool-using LLM workflows, or graph-based state machines in Python.

Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing product value propositions. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint.

Query hyper-local weather from a WeatherFlow Tempest station: current conditions, 7-day forecast, historical observations, and real-time UDP broadcasts. Use when the user asks about the weather, temperature, rain, wind, humidity, forecast, or wants conditions from their own station rather than a generic weather service.

Model software around the business domain using bounded contexts, aggregates, and ubiquitous language. Use when the user mentions "domain modeling", "bounded context", "aggregate root", "ubiquitous language", "anti-corruption layer", "context mapping", "domain events", or "strategic design". Also trigger when splitting a monolith into services, defining microservice boundaries, or aligning code structure with business processes. Covers entities vs value objects, domain events, and context mapping strategies. For architecture layers, see clean-architecture. For complexity, see software-design-philosophy.

Systematic audit of all installed tools, packages, and dependencies for available updates. Covers Homebrew, pip, npm/pnpm, system software updates, git repos, and key CLI tools. Run when the user asks "check if anything needs updating" or similar maintenance queries.

Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users drop off", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", "user activation", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users stop after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound. For habit loops and variable rewards, see hooked-ux. For intrinsic motivation, see drive-motivation.

Manage scheduled cron job pipelines — review overnight runs, detect missed jobs (machine-sleep pattern), run catch-up batches with proper spacing, and integrate results into the morning briefing. Covers the overnight maintenance pipeline common on macOS machines that sleep at night.

Scans modified files for debug leftovers before shipping. Catches console.log, debugger, test URLs, and commented-out code.

Track Apple devices and AirTags via FindMy.app on macOS using AppleScript and screen capture.

Send and receive iMessages/SMS via the imsg CLI on macOS.

Set up and run HeartMuLa, the open-source music generation model family (Suno-like). Generates full songs from lyrics + tags with multilingual support.

Manage Apple Notes via the memo CLI on macOS (create, view, search, edit).

Interact with X/Twitter via xurl, the official X API CLI. Use for posting, replying, quoting, searching, timelines, mentions, likes, reposts, bookmarks, follows, DMs, media upload, and raw v2 endpoint access.

Set up GitHub authentication for the agent using git (universally available) or the gh CLI. Covers HTTPS tokens, SSH keys, credential helpers, and gh auth — with a detection flow to pick the right method automatically.

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.