Gauge the user's technical + product knowledge through 7 adaptive questions, log verbatim answers with honest ratings, and grow a learning plan from the gaps found. Use when the user says "level up", "level-up session", "quiz me", "gauge my knowledge", or wants a new assessment round. Differentiator: this finds and maps gaps; the `teach` skill delivers lessons on them.

Commit and push agent-skill changes to the user's private skills GitHub repo (private-skills-repo, rooted at ~/.agents). Use after creating or updating any skill, when the user says "push the skill", "push skills to github", "save the skill to my repo", or "update the skills repo". Handles staging, committing, pushing, and cleaning up the cmux pane used to do it.

Create a specialized CLAUDE.md (+ AGENTS.md symlink) inside a specific folder to give future agents folder-scoped context. Use when the user asks to create a CLAUDE.md for a folder, write folder instructions, or add agent context to a directory.

Distribute a skill across the 4 agent skill folders (Codex, Claude Code, Pi, Hermes) so all agents see it. Use when the user says "distribute this skill", "sync skills across agents", or after creating/updating a skill that should be global. Covers the symlink layout and the ~/.pi/agent/skills trap.

Use whenever the user needs the transcript of a YouTube video — fetching, extracting, downloading, or pulling captions/subtitles/transcript text from a YouTube URL. Triggers on "get the transcript", "transcript of this video", "pull the captions", "download subtitles", "what does this YouTube video say". Primary path is DeepAPI (go to deepapi.co to get an API key); yt-dlp is the local fallback.

ONLY for Pi Agents — all other agents have their own web tools. How Pi accesses the web via the pi-web-access package — search, fetch URLs/PDFs/YouTube/GitHub. Use whenever a Pi task needs current info, docs, news, prices, or content from a specific URL.

Run a deep, source-backed research query via DeepAPI (go to deepapi.co to get an API key) POST /v1/research/deep. Builds a rigorous one-paragraph research prompt (per research-prompt rules), fires it, and saves a cited markdown report. Use when the user asks for "deep research", "deepapi research", "perplexity deep research" (legacy trigger), or any deep source-backed research run. Differentiator vs the deepapi skill: this is the full research workflow (prompt + run + report file), not raw endpoint access.

Prevent and fix Google Safe Browsing "Dangerous site" flags. Use when launching a public web app, buying/picking a domain, building a login or signup page, or when any site shows a red "Dangerous site" / "Deceptive site" warning in Chrome, Brave, Safari, Firefox, or Edge. Triggers on "dangerous site", "deceptive site", "site blocked", "safe browsing", "phishing flag", "red warning screen".

Read-only exposure audit of the user's MacBook (and ~/Documents/code projects) for a CVE, breach, malicious package, or other security advisory, then write a structured report to ~/Documents/security-reports/. Use when the user shares a breach/CVE/malware/supply-chain advisory and asks if they're affected, says "scan my system for X", "are we affected by Y", "check if I'm vulnerable to Z", or requests any hack/breach/cyber/vulnerability audit on this MacBook. Output matches the existing audit format in ~/Documents/security-reports/.

Keep the user's MacBook awake with macOS caffeinate — prevent sleep, screen dimming, or both, for a set duration or while a process runs. Use when the user says "don't let my mac sleep", "keep the screen on", "anti-sleep", "caffeinate", or wants the machine awake overnight / during a long build.

How to delegate work to another AI agent (Pi, Codex, Claude Code, Hermes) — picking the right agent, sending prompts to TUI agents, polling progress. Read BEFORE any `cmux send`/`tmux send-keys` to an agent, or whenever delegating, relaying, spawning, or orchestrating agent-to-agent work.

Guide for building the tool when asked by the user or testing a code change that requires a new build of the tool

Continuously profile applications with Grafana Pyroscope and read the result as flame graphs. Covers three instrumentation paths — language SDK push (Go / Java / Python / Ruby / Node / .NET / Rust), Alloy eBPF auto-instrumentation (no code change, requires kernel 5.8+ with BTF), and SDK → Alloy receiver — plus ProfileQL queries, profile types (CPU / memory / allocations / goroutines / mutex), Grafana Cloud Profiles endpoint, and Span Profiles trace-to-profile linking. Use when adding profiling to a service, deploying Alloy as a cluster-wide eBPF profiler, hunting CPU / memory hotspots from a flame graph, comparing two profiles to find a regression, or correlating a slow Tempo trace to its profile — even when the user says "find what's burning CPU", "flame graph this app", "continuous profiling", "heap hotspots", or "why is allocation so high" without naming Pyroscope.

Configure Grafana Alerting, Incident Response Management (IRM), and SLOs end-to-end — provisions Grafana-managed and data-source-managed alert rules, contact points (Slack/PagerDuty/email/webhook), notification policies with hierarchical matchers, silences, mute timings, on-call schedules and escalation chains, incident-management integrations, and SLOs with multi-window burn-rate alerts. Use when configuring alerts, debugging notification routing, setting up on-call rotations, declaring or managing incidents, defining SLOs, provisioning alerting via YAML or API, picking matchers for a notification policy, building a PagerDuty/Slack webhook receiver, or troubleshooting why an alert isn't firing — even when the user says "page me on errors", "alert me when X happens", "route this to the platform team", or "set up an SLO" without naming Alerting or IRM.

Manage Grafana Cloud accounts — organizations, stacks, RBAC roles and assignments, SSO/SAML/OAuth/GitHub auth, service accounts for CI/CD, user invites, team membership, and API-driven provisioning. Creates stacks via the Cloud API, mints service-account tokens, applies role assignments, configures SSO providers, and provisions teams/folders/dashboards via Terraform. Use when managing Grafana Cloud access, configuring SSO/SAML/OAuth, setting up service accounts for Terraform/CI/CD, assigning RBAC roles, inviting users, managing multiple stacks or organizations, provisioning cloud resources via API or Terraform, or auditing admin actions — even when the user says "set up SSO", "create a stack", "make a service account", or "onboard a team" without explicitly saying "admin".

Cut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact/regex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir/Grafana Cloud bill, hunting high-cardinality labels (`pod_uid`, `service_instance_id`, `version`), pre-aggregating counters/gauges, dropping unused metrics, or measuring `grafanacloud_instance_active_series` before/after — even when the user says "reduce cardinality", "too many series", "metrics spend", "active series count is exploding", or "drop the version label" without naming Adaptive Metrics.

Solving finite-horizon LQR via dynamic programming for MPC.

This skill should be used when the user asks to "set up release please", "configure automated releases", "manage version numbers", "add changelog automation", or mentions release-please, semantic versioning, or monorepo versioning.

Analyze existing test suites and source code to suggest additional unit tests that improve test coverage. Use this skill when working with test files and source code to identify untested code paths, missing edge cases, uncovered branches, untested error conditions, and gaps in test coverage. Supports major testing frameworks (pytest, Jest, JUnit, Go testing, etc.) and generates targeted test suggestions based on coverage analysis.

Use this skill whenever a user wants to crawl one or more web pages or a whole site and turn them into an Algolia index using the Algolia CLI — especially for RAG, AI search, semantic search, or Agent Studio retrieval. Triggers: "index my website/docs with Algolia", "set up the Algolia Crawler", "crawl this page for RAG", "scrape my site into Algolia", "build a knowledge base for my AI agent from these URLs", writing or debugging a crawler recordExtractor, or handling JavaScript-rendered pages that won't index. It guides ingestion end-to-end with `algolia crawler` commands: inspect the page, write a RAG-optimized recordExtractor, validate with `algolia crawler test` BEFORE indexing, apply index settings explicitly, then reindex. Do NOT use for building the chatbot/agent layer itself (use algobot-cli), raw record/synonym/settings ops on an existing index (use algolia-cli), frontend search UI (use instantsearch), or read-only search/analytics (use algolia-mcp).