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Use when the user wants a quick sanity check for a finite graph claim, construction, or encoding using the lightweight OpenClaw verifier.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Single-agent paper review workflow.
Comprehensive guide and reference for the Antigravity Customization System. Use to explain how customizations work, their loading priority, discovery mechanisms, and to guide the creation of skills, rules, plugins, hooks, and MCP servers.
Provides a comprehensive guide, quick reference, and sitemap for Google Antigravity (AGY), including the Antigravity CLI (agy), Antigravity 2.0, Antigravity IDE, Python SDK, slash commands, keybindings, and customizations (skills, rules, MCP, sidecars). Activate this skill when the user asks questions about how to use, configure, or customize Antigravity, AGY, the agy CLI, the Antigravity IDE, or Antigravity 2.0.
Guidelines for interacting with GitHub and request permissions from the user when commands fail due to restrictions in the agent environment.
ALWAYS use this skill when the user asks to send, get, retrieve, find, share, add, or search for a paper. This skill manages the user's Zotero library with 10,000+ papers and can retrieve PDFs, create share links, add new papers, and search. Prefer this over getscipapers for any request involving sending/getting/finding papers.
Use when the user asks to send, get, retrieve, find, share, add, or search for a paper. This is the live OpenClaw Zotero workflow adapted for Codex and should take priority over external paper retrieval.
| name | graph-verifier |
| description | Use when the user wants a quick sanity check for a finite graph claim, construction, or encoding using the lightweight OpenClaw verifier. |
| metadata | {"short-description":"Lightweight graph claim verification"} |
This skill is installed as an OpenCode-native SKILL.md. For runtime-backed
helpers, prefer the shared ai-agents-skills runtime root and the
AAS_RUNTIME_ROOT override instead of assuming a Codex-specific runtime
path.
On native Windows, use the managed Windows runner and the native runtime command target. Set $runtime to the installed runtime root. Multi-agent installs usually use %LOCALAPPDATA%\ai-agents-skills\runtime. Then run:
$runtime = if ($env:AAS_RUNTIME_ROOT) { $env:AAS_RUNTIME_ROOT } else { "$env:LOCALAPPDATA\ai-agents-skills\runtime" }
& "$runtime\run_skill.bat" "skills/graph-verifier/run_graph_verifier.bat" <args>
POSIX examples below use run_skill.sh and .sh command targets; use the Windows command target above on native Windows.
This uses the managed ai-agents-skills runtime copy of the graph verifier workflow.
For heavier graph-theoretic or algebraic computations, route to sagemath instead.
$AAS_RUNTIME_ROOT/workspace/skills/graph-verifier/Use the managed runtime runner rather than invoking run_graph_verifier.sh directly.
Set AAS_RUNTIME_ROOT to the installed runtime root before using the shared
runner directly.
Shared runner:
runtime_root="${AAS_RUNTIME_ROOT:?Set AAS_RUNTIME_ROOT to the installed runtime root}"; bash "$runtime_root/run_skill.sh"/tmp/graph_input.json.Supported shapes include graph_data, edges, adjacency, and optional expected values.
runtime_root="${AAS_RUNTIME_ROOT:?Set AAS_RUNTIME_ROOT to the installed runtime root}"
bash "$runtime_root/run_skill.sh" skills/graph-verifier/run_graph_verifier.sh --input /tmp/graph_input.json
When this skill is involved, consider this workflow template (install via
the workflow-templates artifact profile, or --with-deps to pull backing skills):
tikz-figure-verification-runbook -- Bounded draw-compile-verify-redraw loop for a TikZ figure that guarantees it is free of overlap, wrong meaning, and bad layout, with Sage-assisted graph realization and fresh-agent visual confirmation before the strict approval gate.