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Found 1,282 Skills
Consult external LLMs (Gemini, OpenAI/Codex, Qwen) for second opinions, alternative plans, independent reviews, or delegated tasks. Use when a user asks for another model's perspective, wants to compare answers, or requests delegating a subtask to Gemini/Codex/Qwen.
Resolve conflicts, negotiate agreements, and mediate disputes between AI agents and humans using Servanda. Use this skill when you need to reach consensus with another party, settle a disagreement, establish shared rules, or create binding agreements through AI-mediated negotiation.
Cross-tool AI consultation. Use when user asks to 'consult gemini', 'ask codex', 'get second opinion', 'cross-check with claude', 'consult another AI', 'ask opencode', 'copilot opinion', or wants a second opinion from a different AI tool.
Query and download logs from Papertrail using the paperctl CLI. Use when: (1) Downloading logs from Taskcluster workers or other systems (2) Searching for specific log entries across systems (3) Investigating CI failures by pulling worker logs (4) Listing available systems or groups in Papertrail Triggers: "papertrail", "pull logs", "worker logs", "download logs", "search logs"
P2P communication between AI agents using walkie-sh CLI. Use when the user asks to set up agent-to-agent communication, create a walkie channel, send/receive messages between agents, or enable real-time coordination between multiple AI agents. Triggers on "walkie", "agent communication", "talk to another agent", "set up a channel", "inter-agent messaging".
Construct and analyze compound-target-disease networks for drug repurposing, polypharmacology discovery, and systems pharmacology. Builds multi-layer networks from ChEMBL, OpenTargets, STRING, DrugBank, Reactome, FAERS, and 60+ other ToolUniverse tools. Calculates Network Pharmacology Scores (0-100), identifies repurposing candidates, predicts mechanisms, and analyzes polypharmacology. Use when users ask about drug repurposing via network analysis, multi-target drug effects, compound-target-disease networks, systems pharmacology, or polypharmacology.
Titanium PurgeTSS utility-first styling toolkit. Use when styling, reviewing, analyzing, or examining Titanium UI with utility classes, configuring config.cjs, creating dynamic components with $.UI.create(), building animations, using grid layouts, setting up icon fonts, or working with TSS styles. Never suggest other CSS framework classes - verify in class-index.md first.
Use when interacting with GitLab from the command line — creating and managing merge requests, issues, CI/CD pipelines, releases, repositories, and any other GitLab operation. Covers all glab CLI commands including mr, issue, ci, release, repo, api, variable, snippet, schedule, stack, label, milestone, incident, and auth.
Use when starting a Next.js Pages Router to App Router migration, evaluating migration feasibility, or auditing codebase readiness. Run this BEFORE any other migration skill.
Evaluate whether a development ticket (user story, feature request, bug report, etc.) is ready for development, and provide specific, actionable feedback if it is not. Use this skill whenever the user asks to triage, evaluate, assess, review, or check the readiness of a ticket, story, issue, or work item. The ticket can come from anywhere: pasted inline, read from a file, fetched from Jira or another tracker via MCP, or any other source. Also use this when a user asks "is this ticket ready?" or "what's wrong with this ticket?" or wants to improve a ticket's specification.
Style, review, and refactoring standards for Bash shell scripting. Trigger when `.sh` files, files with `#!/usr/bin/env bash` or `#!/bin/bash`, or CI workflow blocks with `shell: bash` are created, modified, or reviewed and Bash-specific quality controls (quoting safety, error handling, portability, readability) must be enforced. Do not use for generic POSIX `sh`, PowerShell, or language-specific application style rules. In multi-language pull requests, run together with other applicable `*-style-guide` skills.
Find Cross-Exchange Market Making (XEMM) opportunities by comparing order book depth and liquidity across exchanges. Identifies pairs where one exchange has thin liquidity (ideal for quoting) and another has deep liquidity (ideal for hedging).