Search and read academic papers from arxiv via Semantic Scholar API + ar5iv HTML. No OAuth, no PDF parsing. Use when the user wants to find research papers, read a specific paper, look up citations, or explore academic literature. Trigger on "find papers on", "arxiv", "research on", "look up the paper", "academic search", "semantic scholar", "what does the literature say", "read this paper", or any arxiv/ar5iv URL.
- 📁 assets/
- 📁 evals/
- 📁 references/
- 📄 AGENTS.md
- 📄 checkpoints.yaml
- 📄 CLAUDE.md
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.
Amend the last git commit with a useful, descriptive message. Use when you want to rewrite a commit message, amend commit description, or improve the last commit message.
Abort the current in-progress mission and move to the next one
- 📁 assets/
- 📁 docs/
- 📁 examples/
- 📄 SKILL.md
Research North American mountain peaks and generate comprehensive route beta reports
Use when a request requires repository navigation, code changes, debugging, or structured data analysis and the safest path is to hand execution to a focused subagent.
Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview. This is faster and more reliable than trying to read a raw PDF.
- 📁 assets/
- 📁 references/
- 📄 SKILL.md
Installs, configures, audits, and operates Agent Package Manager (APM) in repositories. Use when initializing apm.yml, installing or updating packages, validating manifests, managing lockfiles, compiling agent context, browsing MCP servers, setting up runtimes, or packaging resolved context for CI and team distribution. Don't use for writing a single skill by hand, generic package managers like npm or pip, or non-APM agent configuration systems.
This skill should be used when the user asks to "test the triage skill", "run triage tests", "validate antithesis triage", "test:triage", or "smoke test triage". Orchestrates end-to-end testing of the antithesis-triage skill by running real triage operations via sub-agents and reviewing the results for bugs, skill compliance issues, and papercuts. --- # Test: Antithesis Triage Skill End-to-end test harness for the `antithesis-triage` skill. Spawn sub-agents that perform real triage operations, then review their work for issues. **The top-level agent MUST NOT use the antithesis-triage skill directly.** All triage operations happen inside sub-agents. The top-level agent only orchestrates and reviews. ## Prerequisites Before starting, verify the same prerequisites the triage skill requires: ```bash which snouty && which agent-browser && which jq ``` Also confirm `ANTITHESIS_TENANT` is set: ```bash echo "$ANTITHESIS_TENANT" ``` If any prerequisite is missing, stop and report which ones are unavailable. ## Phase 1: Discover Runs Spawn a **general-purpose sub-agent** with the Agent tool. Provide these instructions, replacing `{{TENANT}}` with the actual value of the `$ANTITHESIS_TENANT` environment variable and `{{TRIAGE_SKILL}}` with the absolute path to `antithesis-triage/SKILL.md` in this repository: ``` Read the skill file at {{TRIAGE_SKILL}} and follow its instructions to list recent runs for the tenant "{{TENANT}}". Follow the "Summarize recent runs" workflow.
- 📁 .github/
- 📁 agents/
- 📁 assets/
- 📄 .gitignore
- 📄 CHANGELOG.md
- 📄 CONTRIBUTING.md
Build click-through cinematic web showcase pages with dynamic transitions and runtime style switching. Use when users ask for PPT alternatives, interactive launch pages, or high-end storytelling websites with multiple visual styles.
Use for improving LawnBerry Pi AI result quality without breaking the existing backend contract. Covers ai_service review, model artifact or rule improvement, conservative evaluation, performance notes, and avoiding premature accelerator-specific churn.
Production durability patterns for AI agents on the JVM — crash recovery, audit trails, human-in-the-loop, and replay testing using JamJet runtime
